DL_Chatbot.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/fendy07/chatbot-AI/blob/master/DL_Chatbot.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "d18e160a",
      "metadata": {
        "id": "d18e160a"
      },
      "source": [
        "# **AI Chatbot Using Long Short Term Memory Algorithm**\n",
        "\n",
        "<b>Chatbot</b> merupakan bagian dari Natural Language Processing yang digunakan untuk percakapan dengan pengguna melalui teks dan ucapan. Pada praktik hari ini kita akan membuat sebuah chat otomatis atau chatbot tentang program Kampus Merdeka dari Kementerian Pendidikan Kebudayaan Riset dan Teknologi (KEMENDIKBUDRISTEK).\n",
        "\n",
        "Dalam tahapan Chatbot ini ada tahapan yang harus kita perhatikan yaitu,\n",
        "\n",
        "1. Import Library\n",
        "2. Load Dataset\n",
        "3. Preprocessing Data\n",
        "4. Input Length, Output Length and Vocabulary\n",
        "5. Long Short Term Memory Model\n",
        "6. Evaluation Model Analysis\n",
        "7. Testing Chatbot\n",
        "8. Save The Model\n",
        "\n",
        "Dalam proyek ini, kita akan membuat chatbot tentang program Kampus Merdeka!\n",
        "\n",
        "Sumber code: [Medium - Going Merry With Tensorflow 2.0](https://medium.com/analytics-vidhya/chatbot-with-tensorflow-2-0-going-merry-2f79284a6104)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Download Dataset From GitHub**\n",
        "\n",
        "Setelah kita mengetahui apa saja alur yang digunakan untuk membuat proyek AI Chatbot maka tahapan selanjutnya adalah mengunduh atau download dataset dari GitHub milik Fendy Hendriyanto pada bagian repository AI Chatbot. Link: [Chatbot-AI](https://github.com/fendy07/chatbot-AI)"
      ],
      "metadata": {
        "id": "xaowz3BO9B8l"
      },
      "id": "xaowz3BO9B8l"
    },
    {
      "cell_type": "code",
      "source": [
        "# Download dataset kampus_merdeka.json dari GitHub\n",
        "from urllib import request\n",
        "url = \"https://raw.githubusercontent.com/fendy07/chatbot-AI/master/kampus_merdeka.json\"\n",
        "request.urlretrieve(url, \"kampus_merdeka.json\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QEn68nGv9k5e",
        "outputId": "e23bda52-a2d6-4216-867e-06d05424e3a0"
      },
      "id": "QEn68nGv9k5e",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('kampus_merdeka.json', <http.client.HTTPMessage at 0x79d3c0aae470>)"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Load Google Drive**\n",
        "\n",
        "Setelah kita mengunduh dataset dengan library request url dari link yang kita ketahui maka kita akan menyimpan file data yang kita download di Google Drive dengan dengan cara klik pada menu \"**Mount Drive**\" maka akan keluar code dibawah ini.\n",
        "\n",
        "**Notes:** Mohon dirunning terlebih dahulu\n"
      ],
      "metadata": {
        "id": "QRVBAWzMXnGf"
      },
      "id": "QRVBAWzMXnGf"
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kXBRl7ZqXlGD",
        "outputId": "f5239758-26b2-44e5-94b3-bad88c3804c8"
      },
      "id": "kXBRl7ZqXlGD",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Setelah dirunning maka ada notifikasi untuk **Permit this notebook to your access Google Drive** lalu pilih izinkan dan akan diproses ke dalam login akun google kita dan pilih izinkan dan akan keluar seperti gambar dibawah ini.\n",
        "\n",
        "![image.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAcwAAAA0CAYAAAAHbQhGAAAQ2ElEQVR4nO3ca0xT9xsH8C+nQFtpLRQKxcoUReCIXC0KyhwaGWFuOu+4qN2yLTgjLpluMb5xbm92SdgWzaKbLk7n3IR5HYmGDCcS56AKuigFRblYuZaLIKWFnv5faM88AlqoCO7/fN6153DOc37n0Od3PW4JCQl2EEIIIeSxmJEOgBBCCHkeUMIkhBBCnEAJkxBCCHECJUxCCCHECZQwCSGEECdQwiSEEEKcQAmTEEIIcQIlTEIIIcQJlDAJIYQQJ1DCJIQQQpxACZMQQghxAiVMQgghxAmUMAkhhBAnUMIkhBBCnEAJkxBCCHGC+0gHQAgho8WKFSswf/58mEwm7Nq1C9XV1SMdEhlFqIVJhmzbtm3YvXs3UlJSRjqUYcOyLL7++mts374dMplspMP5z2MYBlu3bsXOnTuh1WqfuH9ERAR27NiBL774AhqNxuXzsywLkUgEpVKJ0NBQl49H/luohfmARqPB+++/D19fX1y9ehVZWVn8NpZlkZGRAblcjtLSUuzYsWMEIx3Y9OnTsWLFCnR2duLTTz8d6XCGTXp6OpKSknD27FlkZ2cP67lmzJgBLy8vnDt3Dp2dncN6LleMpnu/fv16hIaGIjc3F3l5eYP6W61WC41GA6PRiEuXLg1ThAMrKyuDRqNBS0sLKioqnvn5yehGCbMfarWa/6cFgKioqOeidaFUKuHt7Y2urq6RDmVYqVQqSKVSuLm5Det5JkyYgMjISLS3t0Ov1w/ruVw1mu694/4MRVJSEtzd3VFSUgKO455yZE92+PBhHD58+JmflzwfqEv2AW9vb0ilUjQ2NsLLywtTp04FcL+LKCwsDA0NDTCbzSMcJXmWtFotFAoF/vnnHxrLegZYlsULL7yAhoYGFBYWjnQ4hPRBLcxHmEwmeHh4IDw8HHl5eYiLi4NSqURxcTESEhLg7e0t2D8pKQmvvPIKVCoVGIZBT08PqqqqcPDgQdTW1vL7rVixAqmpqTh9+rSgBuvoCgaAb775hm/VZmZmIjQ0FPv378fMmTMREREBT09PWK1WlJaWYt++fbBYLIiIiMC6deswZswY/pgvvPAC9u7dK4jz0fOqVCosXboU06ZNg1QqBcdxqKurw2+//YbLly/3KZekpCSkpaVBpVJBJBLxtX9XWwEqlQqvvvoqoqOj4eXlBYZhYLFYcOvWLfzyyy98GTrK72GpqamC77q6urBr1y5cvXrVpZgAQCaTISoqCvfu3UNRUVG/+zAMgwULFmDOnDnw9vYGwzAwm80oKirCr7/+CovFIrjOR8u7o6MDZ8+excmTJwXlOFruveP4FRUVKCkpwaJFi/jnv6WlBYcPH8bFixf5mGNiYgTnTU9PR3p6Ov/ZZDIJnvFHabVavvu7o6Ojz3axWIxly5YhPj6ef1Z6e3v5cn9YZmYmpk2bhpycHJjNZkHslZWV+PHHH1FXVwdAOBzzuFgZhsGWLVswadIknD17FgcOHBCcU6VS4YMPPoC3tzcOHTqEgoICQdyO7n273Y62tjYcP36cKgbPGWphPsJisaC6uhpBQUHQaDRgWRa9vb18C4Nh/i2yN954AzqdDgEBAfz3Hh4emDJlCjZv3oy4uDiXYpFIJNDpdIiNjYWnpycAwNPTE1qtFkuWLBnycTUaDTIzMxEfH893nTEMA41Gg3Xr1mHevHmC/VetWoW1a9dCrVZDJBLx+z9cFkPlGI+Uy+X88cRiMcLDw/Huu+9CLpe7fI6hePHFF6FWq1FTU4OysrI+2xmGwfr167Fo0SIolUo+dqlUitmzZ2POnDn8vhMmTMCmTZv6lLdCocBrr72G9evX9ynL0XLvgfstvzVr1vDXyTAM/Pz8sHLlyqcy0Qa4X0bR0dEDdn/L5XJs3rwZc+fOFTwr7u7uj30OY2NjsXbtWkHsU6ZMgU6nG/Tzy3EcSkpKYLPZEBIS0meYhmVZeHt7o7GxkR9/lclk2LhxI+bOnQuZTAY3NzcwDAOlUgmdToeVK1cOKgYysqiF+UBAQAA8PDwAAAaDAaGhoQgLC0NoaCiqq6vR2toq2D8mJgYJCQkAgAsXLuDIkSNobW2FVqvF8uXLoVQqkZKS4tLEBYZhIJFIUFNTg59++gmNjY14++23ERkZiZCQEADA1atXkZmZCQBISUnBsmXLcOfOHWzfvn3A4y5YsADjxo2D0WjEkSNHUFpaisDAQLz++uuIi4vDSy+9hKKiInR2doJlWcycORMA8Ndff+Ho0aMwmUzQaDTIyMhAQEDAkK8PAHp6elBRUYEzZ87g8uXL6OnpQXJyMhYvXgyVSoXo6GgUFhYKxpYcrZlHW05PC8MwiI2Nhc1mG3DsctGiRYiOjobNZkNxcTFyc3PR0NCA2NhYzJs3Dzabjd934cKFUKlUaGlpQXZ2NvR6PXx8fLBkyRLMmDEDU6dORUJCAs6fPy+IYaTvvYNYLIbFYkFeXh5OnjyJ+Ph4rFy5EmPHjkVYWBiMRqNgIty2bdswbtw45OTkOD3px9H9XVxc3G/398svv4yJEyeis7MTubm5KCgoQE9PD2bNmiVoxT7M3d0dYWFhaGtrw8mTJ1FQUIDU1FQsXLgQarUaISEhqKiogNFoxEcffQRA2OPTH71ejzlz5sDPzw8sy6K4uJjfFh0dDXd3d1y5coUvv5SUFISGhqKtrQ3Hjh3D+fPn4eXlhYULFyIpKQnx8fG4cOECdfk/J6iF+YBIJIKbmxvu3r2La9euwWw2Q6vVQi6Xw2AwoKurC1arFe7u7pDJZHwXYllZGfbu3QuTyQSO41BUVITs7Gx0d3fD398fwcHBQ47JbrejoqICWVlZqKysREdHB/R6PaxW65Bbd76+vvwPz6FDh1BaWgoAqKurw4EDB1BfXw+lUomgoCAA/054MhgM2LNnD0wmEwDAaDQKksJQ7dq1C59//jmKiopgsVjAcRzy8/PR3NwMhmGGPHnEFXFxcRg3bhxu377db5cZwzCIjIwEAJw7dw579uxBXV0dOI7DxYsX8eWXXyI/Px8AEBwcjIkTJ6K7uxvZ2dkoKioCx3EwmUzYu3cvysrKIBaLMWXKFME5RsO9d+jq6kJOTg5ycnJgsVhQWFiIO3fuwM3Nje9xcMXD3d/nzp3rs51hGERERIDjOJw+fRp5eXn8s9La2gq73T7gsW/cuIHPPvsMf/75J99CbG9vh0gk4ivIg9HU1ISqqipIJBJBF7RGo0FQUBDu3r0rqCSHh4ejt7cXJ06cQGFhId8Vf/DgQVRWVkImk2Hy5MmDjoOMDGphPsJsNsNoNKK2thZRUVFoampCaWkpPD09YbPZIBaLoVAoMHbsWHAch5s3b/YZxzMajbh37x6kUqlgfGmwbDYbSkpKBOM5ra2t6O3tHfIx/f39IZfLMWbMGGzevLnffXp6ehAYGIiysjL4+/sDAGpqaoZ8zscJDAzE0qVLER4eDolEIpj56sp1uiIxMREeHh4DztQMDAyETCZDd3c3P4Y3kDFjxsDT0xPt7e2orKwUbOM4Drdv30ZERATGjh0r2DYa7r1Dc3MzXwFweJpLbBITE6FWq1FeXt5v97ejvK1WK6qqqgZ17MrKSjQ1NfGf6+vrsWXLFpfivXjxIiIjIxEcHAxfX1+YTCZERUVBoVCgvLwct27dAnB/tr1CoYCnpyd0Oh10Ol2fY9ntdiiVSpfiIc8OtTAfUCgUgtqywWAAx3Gorq4W/MM9zG63o6en51mF+FQMpXVit9uHJXk5ur9iY2OfyTIRZ7Asi8mTJ6O5ufmJS0lsNpvTrWybzSaYBDQSnsaY89PGMAzi4+Mf2/3tMJjyHk6XLl3CnTt34OPjg4iICAD3nxuO4wTXIBKJRmWZk6GjFuYDDMMIfrDz8vIeO/7S3d0NkUiEsLAw5ObmCrZpNBp4eXnh3r17aGtrE2xTqVSCz/Hx8ZDL5f3OChwObW1tMJvNsFqt2LlzJ18bHkh3dzc/QeVhjtnDroiJiYFSqURXVxdOnDiBgoICPqk4xsGetYdnag5UUWpvb4fFYoFCoUBoaOhjF7j39PTAZrPBx8cH4eHhgh9UhmEwfvx42O12NDY2PvVredRg7/2z8KTub+D+M9jb2wsvL68+z2F0dDQkEskzXfLl6NqdMGECWJZFbW0tNBqNYLIP8G9Pk5eXF/bt2ycY7yTPJ6r+DJJUKoW3tzfKy8thtVoRHh6Od955B76+vmAYBsnJyUhPT4dEIkFlZSU/Ld1qtYLjOAQHByM6OhpyuRw6nQ5paWn8LEhXmc1mcBwHtVqNZcuWQSwW99nHaDSivr4eCoUCb775JmbMmNHvfg63b99Gb28vtFotkpOTIRaLsXjxYrz11lsuv8xBKpWCYRh0d3ejtrYWFosFLMtiw4YNUKvVA/5dd3c3gPuVDWden+YslUqFqVOnPvFFBZ2dnaitrYVIJEJqaipWrVrFL0lgWRabNm3iZ5veuHEDjY2NkEql/NIChmEQGBiIDRs2gGVZdHZ24sqVKy7FPhz3fqgcY/2zZ89+4vjc9OnTH9v9Ddxf4tHc3AyJRIIFCxYgKCgIgYGB/OzTkWjF6fV6tLS0YPLkyZg+fTpkMplgso/DzZs3IRaLsXz5cn6GL3l+UQvzgUdrrk9SWFiIqKgoxMTEIDExEYmJiYLtjY2NOHXqFP/ZYDAgOTkZPj4+2LhxI/+9xWKB1Wp1LfgHysvL0dLSArVajbS0NKSlpfHbHp5R+scffyAoKAjjx49HRkZGn+PU1NTwMy31ej2SkpKgVquxZs0arFmzho+7vr4efn5+Q473xo0b6OrqglKpxIcffthn+0DdwOXl5YiNjYVSqcR7773Hf+/qOkzH7Ee9Xv/EWYunT59GcHAw/P39MX/+fMyfP18QtyMBchyHU6dOQafTQaVSISMjQ1DmNpsNf//9d79jd4MxHPd+qAwGAyZNmoSgoCBs3bqV//7RtY0sy4JlWbS0tDyxO1av1yMkJARBQUH4+OOP+e9bW1vh7u7az1h/a3wB4JNPPgHQ/3PV1NSEa9euYdasWdBqtfykrEfl5+eDZVkEBARg9erVWL16tWD7k9amktGFWpgPSCQS9Pb29lk+4uDoXnHgOA7ffvst8vPz0dHRwdeOzWYziouLkZWVJfjRNRgMOHbsGNra2mC328FxHIxGI3bv3o3m5uancg1NTU34+eefUVVV9dix1cuXLyMrKwsGg+GJ42pNTU344YcfUFtbC47jBHHX19e7FG9paSmOHTuG1tZWcBwHu92Ozs5OFBYWPnYyTUFBAX7//Xe0tLQ8tdenPTxT07Hg/HGqq6uRlZWF4uJimM1m2O12Pv6CggLBMS5duoTvvvtOcF84jkNDQwP279+PQ4cOuRz/cNz7oTp+/DjOnDkj+L/oj6P7W6/XD9j97VBQUICjR4+io6MDdrsdVqsVJSUl+P77759ahXOw9Ho9LBYLVCoVrl+/3m8ly2g04quvvhI8J+T55ZaQkEB3kPzfmzNnDlatWoXr168LXrxPhofjrTgeHh7YsWMHrUMkzwVqYZL/ewzDYNasWQAw6l+y/l+RlJQEPz+/AVtmhIxG1MIkhBBCnEAtTEIIIcQJlDAJIYQQJ1DCJIQQQpxACZMQQghxAiVMQgghxAmUMAkhhBAnUMIkhBBCnEAJkxBCCHECJUxCCCHECZQwCSGEECdQwiSEEEKcQAmTEEIIcQIlTEIIIcQJlDAJIYQQJ1DCJIQQQpxACZMQQghxAiVMQgghxAmUMAkhhBAn/A+3cJ+KmAYqwQAAAABJRU5ErkJggg==)"
      ],
      "metadata": {
        "id": "oJUGMIl6AnKl"
      },
      "id": "oJUGMIl6AnKl"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Instalasi Library Pengenal Suara**\n",
        "\n",
        "Instalasi package sangat diperlukan ketika kita membutuhkan suatu fitur atau library yang akan kita gunakan. Pada proyek AI Chatbot membutuhkan package library yaitu **Speech Recognition** dan **Google Text To Speech** yang harus di install."
      ],
      "metadata": {
        "id": "9ZsdBYNrTfgg"
      },
      "id": "9ZsdBYNrTfgg"
    },
    {
      "cell_type": "code",
      "source": [
        "!pip -q install speechrecognition"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q2lOz2OmFhsz",
        "outputId": "e14147fa-297f-4340-b3d0-a450f2b9c43f"
      },
      "id": "Q2lOz2OmFhsz",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m32.8/32.8 MB\u001b[0m \u001b[31m34.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip -q install gtts"
      ],
      "metadata": {
        "id": "OcZ28yqJFcR8"
      },
      "id": "OcZ28yqJFcR8",
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Notes : Penginstalan dengan tanda -q maksudnya adalah mode quiet atau diam sehingga tidak mengeluarkan output saat eksekusi**"
      ],
      "metadata": {
        "id": "mDpV6eE0DX_f"
      },
      "id": "mDpV6eE0DX_f"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Import Library**\n",
        "\n",
        "Tahapan pertama sebelum melakukan eksplorasi dan praproses pada data adalah memasukan library yang akan digunakan untuk menganalisa dataset dengan menggunakan metode Deep Learning seperti Neural Network dalam pengolahan teks, Chatbot dll. Library yang saya gunakan yaitu NumPy untuk komputasi matematika, Matplotlib untuk visualisasi model data, Natural Language Toolkit atau NLTK untuk pengolahan teks, Pandas untuk membaca data, serta Tensorflow untuk model pada data menggunakan algoritma LSTM (Long Short Term Memory)."
      ],
      "metadata": {
        "id": "MZMVLNyqYTCK"
      },
      "id": "MZMVLNyqYTCK"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "df6e6af3",
      "metadata": {
        "id": "df6e6af3"
      },
      "outputs": [],
      "source": [
        "# Import Libraries\n",
        "import json\n",
        "import nltk\n",
        "import time\n",
        "import random\n",
        "import string\n",
        "import pickle\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from gtts import gTTS\n",
        "from io import BytesIO\n",
        "import tensorflow as tf\n",
        "import IPython.display as ipd\n",
        "import speech_recognition as sr\n",
        "import matplotlib.pyplot as plt\n",
        "from nltk.stem import WordNetLemmatizer\n",
        "from tensorflow.keras.models import Model\n",
        "from keras.utils.vis_utils import plot_model\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.layers import Input, Embedding, LSTM\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
        "from tensorflow.keras.layers import Flatten, Dense, GlobalMaxPool1D"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Download NLTK Package**"
      ],
      "metadata": {
        "id": "XFqXivzfTGhq"
      },
      "id": "XFqXivzfTGhq"
    },
    {
      "cell_type": "code",
      "source": [
        "# Package sentence tokenizer\n",
        "nltk.download('punkt')\n",
        "# Package lemmatization\n",
        "nltk.download('wordnet')\n",
        "# Package multilingual wordnet data\n",
        "nltk.download('omw-1.4')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZFHfBZ3mO1QE",
        "outputId": "5cfea5dc-b1c7-4388-a80e-e6741085dfb5"
      },
      "id": "ZFHfBZ3mO1QE",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Load Dataset Json**\n",
        "\n",
        "Setelah import library, tahapan selanjutnya adalah me-load dataset yang telah disediakan. Dataset yang digunakan berupa format **.json** yang sangat cocok untuk membuat model Chatbot.\n",
        "\n",
        "Data Json merupakan data yang termasuk dalam *semi structured* yang dimana data ini menampung beberapa bagian data seperti **tag**, **pattern**, **context**, dan **response**. Data yang dipakai dalam proyek ini menggunakan dataset manual yang diciptakan oleh student Kampus Merdeka Batch 2 tentang <b>Chatbot Sistem Rekomendasi Kampus Merdeka</b>. [Github](https://github.com/mahmudwhd/WebKadekBot)"
      ],
      "metadata": {
        "id": "gLGpuyY9aMwW"
      },
      "id": "gLGpuyY9aMwW"
    },
    {
      "cell_type": "code",
      "source": [
        "# Importing the dataset\n",
        "with open('/content/kampus_merdeka.json') as content:\n",
        "  data1 = json.load(content)\n",
        "\n",
        "# Mendapatkan semua data ke dalam list\n",
        "tags = [] # data tag\n",
        "inputs = [] # data input atau pattern\n",
        "responses = {} # data respon\n",
        "words = [] # Data kata\n",
        "classes = [] # Data Kelas atau Tag\n",
        "documents = [] # Data Kalimat Dokumen\n",
        "ignore_words = ['?', '!'] # Mengabaikan tanda spesial karakter\n",
        "# Tambahkan data intents dalam json\n",
        "for intent in data1['intents']:\n",
        "  responses[intent['tag']]=intent['responses']\n",
        "  for lines in intent['patterns']:\n",
        "    inputs.append(lines)\n",
        "    tags.append(intent['tag'])\n",
        "    # digunakan untuk pattern atau teks pertanyaan dalam json\n",
        "    for pattern in intent['patterns']:\n",
        "      w = nltk.word_tokenize(pattern)\n",
        "      words.extend(w)\n",
        "      documents.append((w, intent['tag']))\n",
        "      # tambahkan ke dalam list kelas dalam data\n",
        "      if intent['tag'] not in classes:\n",
        "        classes.append(intent['tag'])\n",
        "\n",
        "# Konversi data json ke dalam dataframe\n",
        "data = pd.DataFrame({\"patterns\":inputs, \"tags\":tags})"
      ],
      "metadata": {
        "id": "JD4ILKqFZ_hf"
      },
      "id": "JD4ILKqFZ_hf",
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Cetak data keseluruhan\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "5N0s7BObcv5-",
        "outputId": "58a44006-1146-4ef6-aa06-1e4901f00355"
      },
      "id": "5N0s7BObcv5-",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             patterns  \\\n",
              "0                                               hallo   \n",
              "1                                                 hai   \n",
              "2                                                halo   \n",
              "3                                                 hei   \n",
              "4                                                  hi   \n",
              "..                                                ...   \n",
              "75                                      Apa itu PMMB?   \n",
              "76                        Apa saja persyaratan IISMA?   \n",
              "77  Bagaimana periode pelaksanaan dan cara mendaft...   \n",
              "78           Apa saja manfaat apabila mengikuti PMMB?   \n",
              "79  Apa saja universitas yang tergabung dalam prog...   \n",
              "\n",
              "                            tags  \n",
              "0                       greeting  \n",
              "1                       greeting  \n",
              "2                       greeting  \n",
              "3                       greeting  \n",
              "4                       greeting  \n",
              "..                           ...  \n",
              "75               penjelasan_PMMB  \n",
              "76             persyaratan_IISMA  \n",
              "77  periode_dan_pendaftaran_PMMB  \n",
              "78                  manfaat_PMMB  \n",
              "79                    mitra_PMMB  \n",
              "\n",
              "[80 rows x 2 columns]"
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "      }\n",
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              "\n",
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              "\n",
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              "    domScope.querySelector('#df-d418ccfd-fcb2-4dd2-9145-0cf1b794b6c9 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e5bb53e0-e8cf-45d8-9109-95dc90da7f42 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e5bb53e0-e8cf-45d8-9109-95dc90da7f42');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Cetak data baris pertama sampai baris kelima\n",
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
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        "id": "5DFoJwcVdP52",
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      },
      "id": "5DFoJwcVdP52",
      "execution_count": 10,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "  patterns      tags\n",
              "0    hallo  greeting\n",
              "1      hai  greeting\n",
              "2     halo  greeting\n",
              "3      hei  greeting\n",
              "4       hi  greeting"
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-40eef976-0920-46da-8d5d-5e70d5ebf668 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-40eef976-0920-46da-8d5d-5e70d5ebf668');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Cetak data baris ke-70 sampai baris akhir\n",
        "data.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "HksM_GGVdenI",
        "outputId": "22c5c2b3-5344-4ea7-c5c6-f5665e69062b"
      },
      "id": "HksM_GGVdenI",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             patterns  \\\n",
              "75                                      Apa itu PMMB?   \n",
              "76                        Apa saja persyaratan IISMA?   \n",
              "77  Bagaimana periode pelaksanaan dan cara mendaft...   \n",
              "78           Apa saja manfaat apabila mengikuti PMMB?   \n",
              "79  Apa saja universitas yang tergabung dalam prog...   \n",
              "\n",
              "                            tags  \n",
              "75               penjelasan_PMMB  \n",
              "76             persyaratan_IISMA  \n",
              "77  periode_dan_pendaftaran_PMMB  \n",
              "78                  manfaat_PMMB  \n",
              "79                    mitra_PMMB  "
            ],
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th></th>\n",
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              "    <tr>\n",
              "      <th>75</th>\n",
              "      <td>Apa itu PMMB?</td>\n",
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              "    <tr>\n",
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              "      <td>persyaratan_IISMA</td>\n",
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              "    <tr>\n",
              "      <th>77</th>\n",
              "      <td>Bagaimana periode pelaksanaan dan cara mendaft...</td>\n",
              "      <td>periode_dan_pendaftaran_PMMB</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <td>Apa saja manfaat apabila mengikuti PMMB?</td>\n",
              "      <td>manfaat_PMMB</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>Apa saja universitas yang tergabung dalam prog...</td>\n",
              "      <td>mitra_PMMB</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "              title=\"Suggest charts.\"\n",
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              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-af063994-14dc-405d-b71c-ae942753095d button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f9683293-676f-4a34-9573-6c62542b0681 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f9683293-676f-4a34-9573-6c62542b0681');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Data yang telah kita miliki dalam format JSON yang dapat digunakan melalui pandas dengan cara konversi. Data JSON yang saya miliki didapat dengan cara manual dengan mengambil beberapa referensi website tentang program Kampus Merdeka."
      ],
      "metadata": {
        "id": "8p_YOwTKdr53"
      },
      "id": "8p_YOwTKdr53"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Preprocessing The Data**\n",
        "\n",
        "Setelah kita meload data dan mengonversi data json menjadi dataframe. Tahapan selanjutnya adalah praproses pada dataset yang kita gunakan saat ini yaitu dengan cara:\n",
        "\n",
        "![Praproses.png](data:image/png;base64,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)\n",
        "\n",
        "1.   Remove Punctuations (Menghapus Punktuasi)\n",
        "2.   Lematization (Lematisasi)\n",
        "3.   Tokenization (Tokenisasi)\n",
        "4.   Apply Padding (Padding)\n",
        "5.   Encoding the Outputs (Konversi Keluaran Enkoding)\n",
        "\n",
        "Kelima tahapan pemrosesan teks ini dijelaskan pada bagian langkah selanjutnya."
      ],
      "metadata": {
        "id": "vHnr2WFvebeJ"
      },
      "id": "vHnr2WFvebeJ"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Remove Punctuations**\n",
        "\n",
        "Tahapan praproses pada data teks yang pertama adalah menghapus punktuasi atau tanda baca seperti *special character* yaitu **'!'** (**tanda seru**) **','** (**tanda koma**) **'.'** (**tanda titik sebagai berhenti**) '**?**' (**tanda tanya**) dan tanda baca yang lain. Tahapan ini gunanya untuk mempermudah pemrosesan data teks yang akan kita olah."
      ],
      "metadata": {
        "id": "u_04NeXTIImg"
      },
      "id": "u_04NeXTIImg"
    },
    {
      "cell_type": "code",
      "source": [
        "# Removing Punctuations (Menghilangkan Punktuasi)\n",
        "data['patterns'] = data['patterns'].apply(lambda wrd:[ltrs.lower() for ltrs in wrd if ltrs not in string.punctuation])\n",
        "data['patterns'] = data['patterns'].apply(lambda wrd: ''.join(wrd))"
      ],
      "metadata": {
        "id": "Gh-7EtrfhQgY"
      },
      "id": "Gh-7EtrfhQgY",
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Lemmatization (Lematisasi)**\n",
        "\n",
        "Setelah menghapus punktuasi atau tanda baca, tahapan selanjutnya yaitu Lematisasi atau Lemmatization.\n",
        "\n",
        "**Apa itu Lematisasi?**\n",
        "\n",
        "Lematisasi atau *Lemmatization* adalah proses dimana merujuk pada melakukan sesuatu menggunakan vocabulary atau kosakata dan analisis morfologi kata-kata untuk menghilangkan *inflectional endings only* dan untuk mengembalikan bentuk *dictionary* (kata dalam kamus) dari sebuah kata yang dikenal sebagai ***lemma***.\n",
        "\n",
        "Contoh Lematisasi : **Menggunakan** (Kata Imbuhan) -> **Guna** (Kata Dasar)\n",
        "\n",
        "Dalam contoh berikut proses lematisasi awalnya data teks menggunakan kata imbuhan yaitu **Menggunakan** dimana **meng-** + **guna** (kata dasar yang berawalan vokal g) + **kan** (sebagai akhiran) diubah menjadi kata dasar yaitu '**Guna**'.\n",
        "\n",
        "Proses ini dimana menghilangkan Prefiks pada imbuhan (**Meng-**) dan Suffiks pada (**-kan**)."
      ],
      "metadata": {
        "id": "5brR-qBLJDa_"
      },
      "id": "5brR-qBLJDa_"
    },
    {
      "cell_type": "code",
      "source": [
        "lemmatizer = WordNetLemmatizer()\n",
        "words = [lemmatizer.lemmatize(w.lower()) for w in words if w not in ignore_words]\n",
        "words = sorted(list(set(words)))\n",
        "\n",
        "print (len(words), \"unique lemmatized words\", words)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "22MVRGBsO9gX",
        "outputId": "349af2ad-ebd5-4b2c-eee8-ea2d62ed1a4a"
      },
      "id": "22MVRGBsO9gX",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "78 unique lemmatized words [',', 'afternoon', 'apa', 'apabila', 'bagaimana', 'bai', 'banyak', 'bersertifikat', 'bro', 'buat', 'bumn', 'bye', 'byee', 'cara', 'dadah', 'dah', 'dalam', 'dan', 'good', 'hai', 'hallo', 'halo', 'hei', 'hi', 'hy', 'iisma', 'independen', 'itu', 'jumpa', 'kadek', 'kadekbot', 'kampus', 'kamu', 'kasih', 'kawan', 'kemendikbud', 'kemensos', 'magang', 'mahasiswa', 'makasih', 'malam', 'manfaat', 'mendaftar', 'mengajar', 'mengikuti', 'merdeka', 'mitra', 'morning', 'muda', 'pagi', 'pejuang', 'pelaksanaan', 'pembuatmu', 'penciptamu', 'periode', 'persyaratan', 'pertukaran', 'pmmb', 'program', 'saja', 'sampai', 'see', 'selamat', 'si', 'siang', 'siapa', 'sih', 'sore', 'studi', 'tergabung', 'terima', 'thank', 'thanks', 'tinggal', 'tujuan', 'universitas', 'yang', 'you']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Menyortir Data Kelas Tags**"
      ],
      "metadata": {
        "id": "zmZpqovQE1Zb"
      },
      "id": "zmZpqovQE1Zb"
    },
    {
      "cell_type": "code",
      "source": [
        "# sorting pada data class\n",
        "classes = sorted(list(set(classes)))\n",
        "print (len(classes), \"classes\", classes)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TK_v4Zw5P8rn",
        "outputId": "60fa1e29-892d-46a8-f3dc-881f3743b287"
      },
      "id": "TK_v4Zw5P8rn",
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40 classes ['goodbye', 'greeting', 'kadekbot', 'manfaat_IISMA', 'manfaat_PMMB', 'manfaat_kampus_mengajar', 'manfaat_magang', 'manfaat_pejuang_muda', 'manfaat_pertukaran_mahasiswa', 'manfaat_studi_independen', 'mitra_IISMA', 'mitra_PMMB', 'mitra_magang', 'mitra_studi_independen', 'pencipta_kadekbot', 'penjelasan_IISMA', 'penjelasan_PMMB', 'penjelasan_kampus_mengajar', 'penjelasan_kampus_merdeka', 'penjelasan_magang', 'penjelasan_pejuang_muda', 'penjelasan_pertukaran_mahasiswa', 'penjelasan_studi_independen', 'periode_dan_pendaftaran_IISMA', 'periode_dan_pendaftaran_PMMB', 'periode_dan_pendaftaran_kampus_mengajar', 'periode_dan_pendaftaran_magang', 'periode_dan_pendaftaran_pejuang_muda', 'periode_dan_pendaftaran_pertukaran_mahasiswa', 'periode_dan_pendaftaran_studi_independen', 'persyaratan_IISMA', 'persyaratan_kampus_mengajar', 'persyaratan_kampus_merdeka', 'persyaratan_magang', 'persyaratan_pejuang_muda', 'persyaratan_pertukaran_mahasiswa', 'persyaratan_studi_independen', 'program_kampus_merdeka', 'terimakasih', 'tujuan_kampus_merdeka']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Mencari Jumlah Keseluruhan Data Teks**"
      ],
      "metadata": {
        "id": "u8s3ZKI9FCwo"
      },
      "id": "u8s3ZKI9FCwo"
    },
    {
      "cell_type": "code",
      "source": [
        "# documents = kombinasi antara data pattern dengan data tag dalam intents json\n",
        "print (len(documents), \"documents\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tv5lLFn1QCDP",
        "outputId": "ce6fce3b-3ce3-4cd1-ba24-80ddff419e46"
      },
      "id": "Tv5lLFn1QCDP",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "438 documents\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Tokenization (Tokenisasi)**\n",
        "\n",
        "Setelah proses lematisasi dan mencari tahu data classes dan jumlah keseluruhan data patterns dengan intents-nya. Maka, tahapan selanjutnya proses tokenisasi. **Apa itu Tokenisasi?**\n",
        "\n",
        "Tokenisasi adalah suatu proses memberikan urutan karakter dan sebuah unit dokumen terdefinisi. Tokenisasi juga merupakan tugas untuk memecah kalimat menjadi bagian-bagian yang disebut dengan '**Token**' dan menghilangkan bagian tertentu seperti tanda baca.\n",
        "\n",
        "Contohnya: **Aku Pergi Ke Makassar** -> '**Aku**' '**Pergi**' '**Ke**' '**Makassar**'"
      ],
      "metadata": {
        "id": "sVdv1gW5N7a6"
      },
      "id": "sVdv1gW5N7a6"
    },
    {
      "cell_type": "code",
      "source": [
        "# Tokenize the data (Tokenisasi Data)\n",
        "tokenizer = Tokenizer(num_words=2000)\n",
        "tokenizer.fit_on_texts(data['patterns'])\n",
        "train = tokenizer.texts_to_sequences(data['patterns'])\n",
        "train"
      ],
      "metadata": {
        "id": "Xr5aehymeQdi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c997002a-ff55-4ba2-abe1-aeee26891dc7"
      },
      "id": "Xr5aehymeQdi",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[[40],\n",
              " [41],\n",
              " [42],\n",
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              " [18, 19],\n",
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              " [23, 24, 5],\n",
              " [25, 26],\n",
              " [27],\n",
              " [1, 6, 18, 19],\n",
              " [1, 2, 7, 18, 19],\n",
              " [10, 11, 12, 13, 14, 15, 3, 18, 19],\n",
              " [1, 2, 16, 17, 8, 18, 19],\n",
              " [1, 2, 38, 21, 30, 31, 18, 19],\n",
              " [1, 6, 20, 28],\n",
              " [1, 2, 7, 20, 28],\n",
              " [10, 11, 12, 13, 14, 15, 3, 20, 28],\n",
              " [1, 2, 16, 17, 8, 20, 28],\n",
              " [1, 2, 38, 21, 30, 31, 20, 28],\n",
              " [1, 6, 4, 22],\n",
              " [1, 2, 7, 4, 22],\n",
              " [10, 11, 12, 13, 14, 15, 3, 4, 22],\n",
              " [1, 2, 16, 17, 8, 4, 22],\n",
              " [1, 6, 9],\n",
              " [1, 2, 7, 9],\n",
              " [10, 11, 12, 13, 14, 15, 3, 9],\n",
              " [1, 2, 16, 17, 8, 9],\n",
              " [1, 2, 39, 21, 30, 31, 3, 9],\n",
              " [1, 6, 23, 24, 5],\n",
              " [1, 2, 7, 23, 24, 5],\n",
              " [10, 11, 12, 13, 14, 15, 3, 23, 24, 5],\n",
              " [1, 2, 16, 17, 8, 23, 24, 5],\n",
              " [1, 6, 25, 26],\n",
              " [1, 2, 7, 25, 26],\n",
              " [10, 11, 12, 13, 14, 15, 3, 25, 26],\n",
              " [1, 2, 16, 17, 8, 25, 26],\n",
              " [1, 6, 27],\n",
              " [1, 2, 7, 9],\n",
              " [10, 11, 12, 13, 14, 15, 3, 27],\n",
              " [1, 2, 16, 17, 8, 27],\n",
              " [1, 2, 39, 21, 30, 31, 3, 27]]"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Padding**\n",
        "\n",
        "Setelah memproses tokenisasi yang dimana memecah kalimat menajdi bagian-bagian yang disebut token yang digunakan untuk mengolah data teks pada AI Chatbot maka tahapan selanjutnya adalah Padding.\n",
        "\n",
        "**Apa itu Padding?**\n",
        "\n",
        "**Padding** adalah Suatu proses untuk mengubah setiap sequence agar memiliki panjang yang sama. Pada padding, setiap sequence dibuat sama panjang dengan menambahkan nilai 0 secara suffiks atau prefiks hingga mencapai panjang maksimum sequence. Selain itu padding juga dapat memotong sequence hingga panjangnya sesuai dengan panjang maksimum sequence.\n",
        "\n",
        "Padding juga adalah proses untuk membuat setiap kalimat pada teks memiliki panjang yang seragam. Sama seperti melakukan resize gambar, agar resolusi setiap gambar sama besar. Untuk menggunakan padding bisa impor library **pad_sequence**. Kemudian buat panggil fungsi pad_sequence() dan masukkan sequence hasil tokenisasi sebagai parameternya.\n",
        "\n",
        "Contohnya: `sequences_samapanjang = pad_sequences(sequences)`\n",
        "\n",
        "Yang nantinya akan dikeluarkan menjadi angka dengan awalan 0 seperti gambar dibawah ini.\n",
        "\n",
        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      ],
      "metadata": {
        "id": "LfEpFf0hPOUZ"
      },
      "id": "LfEpFf0hPOUZ"
    },
    {
      "cell_type": "code",
      "source": [
        "# Melakukan proses padding pada data\n",
        "x_train = pad_sequences(train)\n",
        "# Menampilkan hasil padding\n",
        "print(x_train)"
      ],
      "metadata": {
        "id": "5BQdPUTNvS1t",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "36db6838-4dae-4557-eaf8-207c9b8ac139"
      },
      "id": "5BQdPUTNvS1t",
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0  0  0  0  0  0  0  0  0 40]\n",
            " [ 0  0  0  0  0  0  0  0  0 41]\n",
            " [ 0  0  0  0  0  0  0  0  0 42]\n",
            " [ 0  0  0  0  0  0  0  0  0 43]\n",
            " [ 0  0  0  0  0  0  0  0  0 44]\n",
            " [ 0  0  0  0  0  0  0  0  0 45]\n",
            " [ 0  0  0  0  0  0  0  0  0 46]\n",
            " [ 0  0  0  0  0  0  0  0  0 47]\n",
            " [ 0  0  0  0  0  0  0  0  0 48]\n",
            " [ 0  0  0  0  0  0  0  0  0 49]\n",
            " [ 0  0  0  0  0  0  0  0  0 50]\n",
            " [ 0  0  0  0  0  0  0  0  0 51]\n",
            " [ 0  0  0  0  0  0  0  0  0 52]\n",
            " [ 0  0  0  0  0  0  0  0  0 53]\n",
            " [ 0  0  0  0  0  0  0  0  0 54]\n",
            " [ 0  0  0  0  0  0  0  1  6 32]\n",
            " [ 0  0  0  0  0  0  0  0 29 32]\n",
            " [ 0  0  0  0  0  0  0  0 29 55]\n",
            " [ 0  0  0  0 33 21 56 57 29 58]\n",
            " [ 0  0  0  0  0  0  0 29 59 33]\n",
            " [ 0  0  0  0  0  0  0  0  0 60]\n",
            " [ 0  0  0  0  0  0  0  0  0 61]\n",
            " [ 0  0  0  0  0  0  0  0  0 34]\n",
            " [ 0  0  0  0  0  0  0  0  0 62]\n",
            " [ 0  0  0  0  0  0  0  0 63 34]\n",
            " [ 0  0  0  0  0  0  0  0 64 65]\n",
            " [ 0  0  0  0  0  0  0  0 66 67]\n",
            " [ 0  0  0  0  0  0  0  0  0 68]\n",
            " [ 0  0  0  0  0  0  0  0 69 35]\n",
            " [ 0  0  0  0  0  0  0  0  0 70]\n",
            " [ 0  0  0  0  0  0  0  0 71 35]\n",
            " [ 0  0  0  0  0  0  0  0 36 37]\n",
            " [ 0  0  0  0  0  0  0  0  0 72]\n",
            " [ 0  0  0  0  0  0  0 36 37 73]\n",
            " [ 0  0  0  0  0  0  1  6  4  5]\n",
            " [ 0  0  0  0  0  0  1 74  4  5]\n",
            " [ 0  0  0  0  0  1  7  8  4  5]\n",
            " [ 0  0  0  0  0  1  2  3  4  5]\n",
            " [ 0  0  0  0  0  0  3  4  5 75]\n",
            " [ 0  0  0  0  0  0  3  4  5 76]\n",
            " [ 0  0  0  0  0  0  3  4  5 77]\n",
            " [ 0  0  0  0  0  0  0  0 18 19]\n",
            " [ 0  0  0  0  0  0  0  0  0 20]\n",
            " [ 0  0  0  0  0  0  0  0  4 22]\n",
            " [ 0  0  0  0  0  0  0  0  0  9]\n",
            " [ 0  0  0  0  0  0  0 23 24  5]\n",
            " [ 0  0  0  0  0  0  0  0 25 26]\n",
            " [ 0  0  0  0  0  0  0  0  0 27]\n",
            " [ 0  0  0  0  0  0  1  6 18 19]\n",
            " [ 0  0  0  0  0  1  2  7 18 19]\n",
            " [ 0 10 11 12 13 14 15  3 18 19]\n",
            " [ 0  0  0  1  2 16 17  8 18 19]\n",
            " [ 0  0  1  2 38 21 30 31 18 19]\n",
            " [ 0  0  0  0  0  0  1  6 20 28]\n",
            " [ 0  0  0  0  0  1  2  7 20 28]\n",
            " [ 0 10 11 12 13 14 15  3 20 28]\n",
            " [ 0  0  0  1  2 16 17  8 20 28]\n",
            " [ 0  0  1  2 38 21 30 31 20 28]\n",
            " [ 0  0  0  0  0  0  1  6  4 22]\n",
            " [ 0  0  0  0  0  1  2  7  4 22]\n",
            " [ 0 10 11 12 13 14 15  3  4 22]\n",
            " [ 0  0  0  1  2 16 17  8  4 22]\n",
            " [ 0  0  0  0  0  0  0  1  6  9]\n",
            " [ 0  0  0  0  0  0  1  2  7  9]\n",
            " [ 0  0 10 11 12 13 14 15  3  9]\n",
            " [ 0  0  0  0  1  2 16 17  8  9]\n",
            " [ 0  0  1  2 39 21 30 31  3  9]\n",
            " [ 0  0  0  0  0  1  6 23 24  5]\n",
            " [ 0  0  0  0  1  2  7 23 24  5]\n",
            " [10 11 12 13 14 15  3 23 24  5]\n",
            " [ 0  0  1  2 16 17  8 23 24  5]\n",
            " [ 0  0  0  0  0  0  1  6 25 26]\n",
            " [ 0  0  0  0  0  1  2  7 25 26]\n",
            " [ 0 10 11 12 13 14 15  3 25 26]\n",
            " [ 0  0  0  1  2 16 17  8 25 26]\n",
            " [ 0  0  0  0  0  0  0  1  6 27]\n",
            " [ 0  0  0  0  0  0  1  2  7  9]\n",
            " [ 0  0 10 11 12 13 14 15  3 27]\n",
            " [ 0  0  0  0  1  2 16 17  8 27]\n",
            " [ 0  0  1  2 39 21 30 31  3 27]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Hasil setelah padding adalah setiap sequence memiliki panjang yang sama. Padding dapat melakukan ini dengan menambahkan 0 secara default pada awal sequence yang lebih pendek."
      ],
      "metadata": {
        "id": "1Khg-ygkb0nD"
      },
      "id": "1Khg-ygkb0nD"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Encoding Text**\n",
        "\n",
        "Setelah tahapan proses Padding pada suatu teks maka proses terakhir dalam pemrosesan teks adalah tahapan Encoding.\n",
        "\n",
        "**Apa itu Encoding?**\n",
        "\n",
        "**Encoding** merupakan suatu konversi atau pengkodean yang dimana data kategorik seperti huruf atau data teks menjadi data numerik atau angka menyesuaikan dengan data label yang digunakan. Pada proses tahapan ini, encoding mengubah data teks pada kolom data tags menjadi data numerik dengan bahasa biner komputer yaitu 0 dan 1.\n",
        "\n",
        "Tujuan dari encoding ini adalah mempermudah saat proses komputasi data teks dan modelling."
      ],
      "metadata": {
        "id": "qY0vxxwBPeJC"
      },
      "id": "qY0vxxwBPeJC"
    },
    {
      "cell_type": "code",
      "source": [
        "# Melakukan konversi data label tags dengan encoding\n",
        "le = LabelEncoder()\n",
        "y_train = le.fit_transform(data['tags'])\n",
        "print(y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sczq--IpTYWa",
        "outputId": "7f8a3277-332a-4c0d-fc78-97be271d6889"
      },
      "id": "sczq--IpTYWa",
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[ 1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  2  2 14 14 14  0  0  0  0\n",
            "  0  0  0  0  0 38 38 38 38 38 18 39 32 37 37 37 37 37 37 37 37 37 37 37\n",
            " 22 36 29  9 13 19 33 26  6 12 17 31 25  5 15 30 23  3 10 21 35 28  8 20\n",
            " 34 27  7 16 30 24  4 11]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Tokenizer pada Tensorflow memberikan token unik untuk setiap kata yang berbeda. Dan juga padding dilakukan untuk mendapatkan semua data dengan panjang yang sama sehingga dapat mengirimkannya ke lapisan atau layer model LSTM. variabel target juga dikodekan menjadi nilai desimal."
      ],
      "metadata": {
        "id": "D9rKggGCgnjT"
      },
      "id": "D9rKggGCgnjT"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Input Length, Output Length and Vocabulary**"
      ],
      "metadata": {
        "id": "_hE21zfRhiNS"
      },
      "id": "_hE21zfRhiNS"
    },
    {
      "cell_type": "code",
      "source": [
        "# Melihat hasil input pada data teks\n",
        "input_shape = x_train.shape[1]\n",
        "print(input_shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dbtBZXFvgvCB",
        "outputId": "fc2aa3e3-1890-4d0d-8b76-4e657e680ad9"
      },
      "id": "dbtBZXFvgvCB",
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Melakukan definisi tiap kalimat dan kata pada data teks\n",
        "vocabulary = len(tokenizer.word_index)\n",
        "print(\"number of unique words : \", vocabulary)\n",
        "\n",
        "# Melakukan pemeriksaan pada data output label teks\n",
        "output_length = le.classes_.shape[0]\n",
        "print(\"output length: \", output_length)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "310y6oNLhuzv",
        "outputId": "185ca977-f65f-41b0-94c9-38f418e9fb69"
      },
      "id": "310y6oNLhuzv",
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "number of unique words :  77\n",
            "output length:  40\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Input length** dan **output length** terlihat sangat jelas hasilnya. Mereka adalah untuk bentuk input dan bentuk output dari data train atau latih yang akan diproses pada algoritma LSTM yang akan dilatih.\n",
        "\n",
        "**Vocabulary Size** adalah untuk lapisan penyematan untuk membuat representasi vektor unik untuk setiap kata."
      ],
      "metadata": {
        "id": "AInHhmVGict2"
      },
      "id": "AInHhmVGict2"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Save Model Words & Classes**\n",
        "\n",
        "Setelah dilakukan pemrosesan teks yang dilakukan lima tahap maka kita bisa simpan model pemrosesan teks tersebut dengan menggunakan format pickle.\n",
        "\n",
        "Hal ini biasanya digunakan untuk membuat hubungan model yang telah dilatih dengan model pemrosesan teks."
      ],
      "metadata": {
        "id": "1LxIElYjQbB7"
      },
      "id": "1LxIElYjQbB7"
    },
    {
      "cell_type": "code",
      "source": [
        "# Simpan hasil pemrosesan teks dengan menggunakan pickle\n",
        "pickle.dump(words, open('words.pkl','wb'))\n",
        "pickle.dump(classes, open('classes.pkl','wb'))"
      ],
      "metadata": {
        "id": "wYV77QFbQVLP"
      },
      "id": "wYV77QFbQVLP",
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Save Label Encoder & Tokenizer**"
      ],
      "metadata": {
        "id": "dY9COWCwexgZ"
      },
      "id": "dY9COWCwexgZ"
    },
    {
      "cell_type": "code",
      "source": [
        "pickle.dump(le, open('le.pkl','wb'))\n",
        "pickle.dump(tokenizer, open('tokenizers.pkl','wb'))"
      ],
      "metadata": {
        "id": "saM3QTSjewR4"
      },
      "id": "saM3QTSjewR4",
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Long Short Term Memory (LSTM) Model**\n",
        "\n",
        "Setelah menyimpan model untuk hasil pemrosesan teks, tahapan selanjutnya adalah melakukan modelling atau pemodelan untuk Chatbot dengan menggunakan algoritma LSTM (Long Short Term Memory).\n",
        "\n",
        "**Apa itu Algoritma LSTM?**\n",
        "\n",
        "**LSTM (Long Short Term Memory)** merupakan algoritma Deep Learning yang populer dan cocok digunakan untuk membuat prediksi dan klasifikasi yang berhubungan dengan waktu dan data teks.\n",
        "\n",
        "Algoritma ini bisa dikatakan pengembangan atau salah satu jenis dari algoritma RNN (Recurrent Neural Network). Dalam algoritma RNN, output dari langkah terakhir diumpankan kembali sebagai input pada langkah yang sedang aktif. Namun, algoritma RNN memiliki kekurangan yaitu tidak dapat memprediksi kata yang disimpan dalam memori jangka panjang.\n",
        "\n",
        "Nah, algoritma LSTM dirancang untuk mengatasi kelemahan tersebut, namun tetap mempertahankan kelebihan yang ada pada algoritma RNN dimana RNN mampu memberikan prediksi yang lebih akurat dari informasi terbaru.\n",
        "\n",
        "Algoritma LSTM pertama kali dikembangkan oleh Hochreiter dan Schmidhuber.  Algoritma ini mampu menyimpan informasi untuk jangka waktu yang lama. Hal ini kemudian dapat digunakan untuk memproses, memprediksi, dan mengklasifikasikan informasi berdasarkan data deret waktu.\n",
        "\n",
        "Struktur algoritma LSTM terdiri atas neural network dan beberapa blok memori yang berbeda. Blok memori ini disebut sebagai cell.  State dari cell dan hidden state akan diteruskan ke cell berikutnya.\n",
        "\n",
        "Seperti yang ditunjukkan pada gambar di bawah, bangun berbentuk persegi panjang berwarna biru adalah **ilustrasi cell** pada LSTM.\n",
        "\n",
        "![LSTM_deep_learning_algorithms.webp](data:image/webp;base64,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)\n",
        "\n",
        "Informasi yang dikumpulkan oleh algoritma LSTM kemudian akan disimpan oleh cell dan manipulasi memori dilakukan oleh komponen yang disebut dengan gate. Ada tiga jenis gate pada algoritma LSTM, di antaranya  Forget gate, Input gate, dan  Output gate. Sumber : [Trivusi](https://www.trivusi.web.id/2022/07/algoritma-lstm.html)\n",
        "\n",
        "Jaringan syaraf dalam kasus chatbot ini yang terdiri dari lapisan atau *layer* embedding yang merupakan salah satu hal yang paling kuat di bidang pemrosesan bahasa alami atau NLP. output atau keluaran dari lapisan (*layer*) embedding adalah input (masukan) data teks dari lapisan berulang (*recurrent*) dengan layer LSTM gate (Lapisan Gerbang **Long Shot Term Memory)**. Kemudian, output atau keluaran diratakan dan lapisan Dense digunakan dengan fungsi aktivasi **Softmax** yang dimana implementasi chatbot ini memiliki data label lebih dari dua kelas.\n",
        "\n",
        "Bagian utama dalam pemodelan chatbot ini adalah lapisan embedding yang memberikan nilai vektor yang sesuai untuk setiap kata dalam data teks yang telah dimasukkan."
      ],
      "metadata": {
        "id": "BI7OvNariInQ"
      },
      "id": "BI7OvNariInQ"
    },
    {
      "cell_type": "code",
      "source": [
        "# Creating the model (Membuat Modelling)\n",
        "i = Input(shape=(input_shape,)) # Layer Input\n",
        "x = Embedding(vocabulary+1,10)(i) # Layer Embedding\n",
        "x = LSTM(10, return_sequences=True, recurrent_dropout=0.2)(x) # Layer Long Short Term Memory\n",
        "x = Flatten()(x) # Layer Flatten\n",
        "x = Dense(output_length, activation=\"softmax\")(x) # Layer Dense\n",
        "model  = Model(i,x) # Model yang telah disusun dari layer Input sampai layer Output\n",
        "\n",
        "# Compiling the model (Kompilasi Model)\n",
        "model.compile(loss=\"sparse_categorical_crossentropy\", optimizer='adam', metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "2XBG3_reh2KY"
      },
      "id": "2XBG3_reh2KY",
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualization Plot Architecture Model (Visualisasi Plot Arsitektur Model)\n",
        "plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 533
        },
        "id": "SO1blkS7ZzuH",
        "outputId": "72e10cc5-b628-48cf-b6cc-74e3d461ef40"
      },
      "id": "SO1blkS7ZzuH",
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Menampilkan parameter pada model LSTM\n",
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4hab_JHoopQI",
        "outputId": "8e1aedaf-0746-4e6b-a45c-a3620d853c8e"
      },
      "id": "4hab_JHoopQI",
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " input_1 (InputLayer)        [(None, 10)]              0         \n",
            "                                                                 \n",
            " embedding (Embedding)       (None, 10, 10)            780       \n",
            "                                                                 \n",
            " lstm (LSTM)                 (None, 10, 10)            840       \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 100)               0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 40)                4040      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 5,660\n",
            "Trainable params: 5,660\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Training the model (Melatih model data sampai 450 kali)\n",
        "train = model.fit(x_train, y_train, epochs=450)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AHtOlCb8kGgZ",
        "outputId": "ee62a778-3aaf-4be6-d756-42781211ab44"
      },
      "id": "AHtOlCb8kGgZ",
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/450\n",
            "3/3 [==============================] - 4s 23ms/step - loss: 3.6870 - accuracy: 0.0000e+00\n",
            "Epoch 2/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 3.6799 - accuracy: 0.1000\n",
            "Epoch 3/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 3.6729 - accuracy: 0.1250\n",
            "Epoch 4/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 3.6651 - accuracy: 0.1250\n",
            "Epoch 5/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.6555 - accuracy: 0.1125\n",
            "Epoch 6/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 3.6447 - accuracy: 0.1375\n",
            "Epoch 7/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.6317 - accuracy: 0.1500\n",
            "Epoch 8/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.6163 - accuracy: 0.1500\n",
            "Epoch 9/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 3.5971 - accuracy: 0.1250\n",
            "Epoch 10/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.5748 - accuracy: 0.1375\n",
            "Epoch 11/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.5460 - accuracy: 0.1375\n",
            "Epoch 12/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 3.5153 - accuracy: 0.1375\n",
            "Epoch 13/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.4775 - accuracy: 0.1500\n",
            "Epoch 14/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.4323 - accuracy: 0.1500\n",
            "Epoch 15/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 3.3769 - accuracy: 0.1500\n",
            "Epoch 16/450\n",
            "3/3 [==============================] - 0s 27ms/step - loss: 3.3181 - accuracy: 0.1625\n",
            "Epoch 17/450\n",
            "3/3 [==============================] - 0s 31ms/step - loss: 3.2478 - accuracy: 0.2375\n",
            "Epoch 18/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 3.1718 - accuracy: 0.2625\n",
            "Epoch 19/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 3.1019 - accuracy: 0.2250\n",
            "Epoch 20/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 3.0189 - accuracy: 0.2375\n",
            "Epoch 21/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 2.9541 - accuracy: 0.2250\n",
            "Epoch 22/450\n",
            "3/3 [==============================] - 0s 23ms/step - loss: 2.9048 - accuracy: 0.2000\n",
            "Epoch 23/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 2.8655 - accuracy: 0.2000\n",
            "Epoch 24/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 2.8542 - accuracy: 0.1875\n",
            "Epoch 25/450\n",
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            "3/3 [==============================] - 0s 33ms/step - loss: 0.3231 - accuracy: 0.9500\n",
            "Epoch 379/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 0.3280 - accuracy: 0.9500\n",
            "Epoch 380/450\n",
            "3/3 [==============================] - 0s 33ms/step - loss: 0.3295 - accuracy: 0.9500\n",
            "Epoch 381/450\n",
            "3/3 [==============================] - 0s 33ms/step - loss: 0.3285 - accuracy: 0.9500\n",
            "Epoch 382/450\n",
            "3/3 [==============================] - 0s 30ms/step - loss: 0.3236 - accuracy: 0.9500\n",
            "Epoch 383/450\n",
            "3/3 [==============================] - 0s 27ms/step - loss: 0.3219 - accuracy: 0.9750\n",
            "Epoch 384/450\n",
            "3/3 [==============================] - 0s 26ms/step - loss: 0.3173 - accuracy: 0.9625\n",
            "Epoch 385/450\n",
            "3/3 [==============================] - 0s 26ms/step - loss: 0.3177 - accuracy: 0.9625\n",
            "Epoch 386/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 0.3149 - accuracy: 0.9625\n",
            "Epoch 387/450\n",
            "3/3 [==============================] - 0s 40ms/step - loss: 0.3121 - accuracy: 0.9375\n",
            "Epoch 388/450\n",
            "3/3 [==============================] - 0s 24ms/step - loss: 0.3149 - accuracy: 0.9625\n",
            "Epoch 389/450\n",
            "3/3 [==============================] - 0s 39ms/step - loss: 0.3150 - accuracy: 0.9500\n",
            "Epoch 390/450\n",
            "3/3 [==============================] - 0s 47ms/step - loss: 0.3088 - accuracy: 0.9625\n",
            "Epoch 391/450\n",
            "3/3 [==============================] - 0s 59ms/step - loss: 0.3099 - accuracy: 0.9500\n",
            "Epoch 392/450\n",
            "3/3 [==============================] - 0s 36ms/step - loss: 0.3106 - accuracy: 0.9375\n",
            "Epoch 393/450\n",
            "3/3 [==============================] - 0s 43ms/step - loss: 0.3104 - accuracy: 0.9375\n",
            "Epoch 394/450\n",
            "3/3 [==============================] - 0s 30ms/step - loss: 0.3068 - accuracy: 0.9625\n",
            "Epoch 395/450\n",
            "3/3 [==============================] - 0s 30ms/step - loss: 0.2986 - accuracy: 0.9625\n",
            "Epoch 396/450\n",
            "3/3 [==============================] - 0s 47ms/step - loss: 0.3037 - accuracy: 0.9625\n",
            "Epoch 397/450\n",
            "3/3 [==============================] - 0s 33ms/step - loss: 0.2987 - accuracy: 0.9625\n",
            "Epoch 398/450\n",
            "3/3 [==============================] - 0s 41ms/step - loss: 0.2996 - accuracy: 0.9875\n",
            "Epoch 399/450\n",
            "3/3 [==============================] - 0s 32ms/step - loss: 0.2935 - accuracy: 0.9750\n",
            "Epoch 400/450\n",
            "3/3 [==============================] - 0s 26ms/step - loss: 0.3014 - accuracy: 0.9625\n",
            "Epoch 401/450\n",
            "3/3 [==============================] - 0s 34ms/step - loss: 0.2927 - accuracy: 0.9625\n",
            "Epoch 402/450\n",
            "3/3 [==============================] - 0s 48ms/step - loss: 0.2859 - accuracy: 1.0000\n",
            "Epoch 403/450\n",
            "3/3 [==============================] - 0s 29ms/step - loss: 0.2926 - accuracy: 0.9625\n",
            "Epoch 404/450\n",
            "3/3 [==============================] - 0s 34ms/step - loss: 0.2905 - accuracy: 0.9750\n",
            "Epoch 405/450\n",
            "3/3 [==============================] - 0s 36ms/step - loss: 0.2863 - accuracy: 0.9875\n",
            "Epoch 406/450\n",
            "3/3 [==============================] - 0s 45ms/step - loss: 0.2860 - accuracy: 0.9750\n",
            "Epoch 407/450\n",
            "3/3 [==============================] - 0s 40ms/step - loss: 0.2810 - accuracy: 0.9875\n",
            "Epoch 408/450\n",
            "3/3 [==============================] - 0s 43ms/step - loss: 0.2773 - accuracy: 0.9750\n",
            "Epoch 409/450\n",
            "3/3 [==============================] - 0s 32ms/step - loss: 0.2826 - accuracy: 0.9750\n",
            "Epoch 410/450\n",
            "3/3 [==============================] - 0s 30ms/step - loss: 0.2765 - accuracy: 0.9750\n",
            "Epoch 411/450\n",
            "3/3 [==============================] - 0s 34ms/step - loss: 0.2815 - accuracy: 0.9750\n",
            "Epoch 412/450\n",
            "3/3 [==============================] - 0s 45ms/step - loss: 0.2774 - accuracy: 0.9750\n",
            "Epoch 413/450\n",
            "3/3 [==============================] - 0s 49ms/step - loss: 0.2731 - accuracy: 0.9875\n",
            "Epoch 414/450\n",
            "3/3 [==============================] - 0s 65ms/step - loss: 0.2743 - accuracy: 0.9875\n",
            "Epoch 415/450\n",
            "3/3 [==============================] - 0s 42ms/step - loss: 0.2686 - accuracy: 0.9875\n",
            "Epoch 416/450\n",
            "3/3 [==============================] - 0s 41ms/step - loss: 0.2721 - accuracy: 0.9625\n",
            "Epoch 417/450\n",
            "3/3 [==============================] - 0s 38ms/step - loss: 0.2702 - accuracy: 0.9750\n",
            "Epoch 418/450\n",
            "3/3 [==============================] - 0s 34ms/step - loss: 0.2693 - accuracy: 0.9750\n",
            "Epoch 419/450\n",
            "3/3 [==============================] - 0s 54ms/step - loss: 0.2650 - accuracy: 0.9875\n",
            "Epoch 420/450\n",
            "3/3 [==============================] - 0s 43ms/step - loss: 0.2644 - accuracy: 0.9875\n",
            "Epoch 421/450\n",
            "3/3 [==============================] - 0s 31ms/step - loss: 0.2636 - accuracy: 0.9875\n",
            "Epoch 422/450\n",
            "3/3 [==============================] - 0s 48ms/step - loss: 0.2647 - accuracy: 0.9875\n",
            "Epoch 423/450\n",
            "3/3 [==============================] - 0s 53ms/step - loss: 0.2596 - accuracy: 0.9875\n",
            "Epoch 424/450\n",
            "3/3 [==============================] - 0s 48ms/step - loss: 0.2606 - accuracy: 0.9750\n",
            "Epoch 425/450\n",
            "3/3 [==============================] - 0s 43ms/step - loss: 0.2562 - accuracy: 0.9875\n",
            "Epoch 426/450\n",
            "3/3 [==============================] - 0s 41ms/step - loss: 0.2562 - accuracy: 0.9875\n",
            "Epoch 427/450\n",
            "3/3 [==============================] - 0s 44ms/step - loss: 0.2521 - accuracy: 0.9625\n",
            "Epoch 428/450\n",
            "3/3 [==============================] - 0s 38ms/step - loss: 0.2519 - accuracy: 0.9875\n",
            "Epoch 429/450\n",
            "3/3 [==============================] - 0s 45ms/step - loss: 0.2522 - accuracy: 0.9875\n",
            "Epoch 430/450\n",
            "3/3 [==============================] - 0s 50ms/step - loss: 0.2551 - accuracy: 0.9750\n",
            "Epoch 431/450\n",
            "3/3 [==============================] - 0s 51ms/step - loss: 0.2478 - accuracy: 1.0000\n",
            "Epoch 432/450\n",
            "3/3 [==============================] - 0s 48ms/step - loss: 0.2448 - accuracy: 1.0000\n",
            "Epoch 433/450\n",
            "3/3 [==============================] - 0s 43ms/step - loss: 0.2478 - accuracy: 1.0000\n",
            "Epoch 434/450\n",
            "3/3 [==============================] - 0s 63ms/step - loss: 0.2464 - accuracy: 1.0000\n",
            "Epoch 435/450\n",
            "3/3 [==============================] - 0s 43ms/step - loss: 0.2369 - accuracy: 0.9875\n",
            "Epoch 436/450\n",
            "3/3 [==============================] - 0s 65ms/step - loss: 0.2379 - accuracy: 0.9875\n",
            "Epoch 437/450\n",
            "3/3 [==============================] - 0s 42ms/step - loss: 0.2429 - accuracy: 0.9875\n",
            "Epoch 438/450\n",
            "3/3 [==============================] - 0s 37ms/step - loss: 0.2439 - accuracy: 1.0000\n",
            "Epoch 439/450\n",
            "3/3 [==============================] - 0s 49ms/step - loss: 0.2421 - accuracy: 1.0000\n",
            "Epoch 440/450\n",
            "3/3 [==============================] - 0s 25ms/step - loss: 0.2369 - accuracy: 0.9750\n",
            "Epoch 441/450\n",
            "3/3 [==============================] - 0s 30ms/step - loss: 0.2384 - accuracy: 0.9875\n",
            "Epoch 442/450\n",
            "3/3 [==============================] - 0s 44ms/step - loss: 0.2350 - accuracy: 1.0000\n",
            "Epoch 443/450\n",
            "3/3 [==============================] - 0s 33ms/step - loss: 0.2353 - accuracy: 1.0000\n",
            "Epoch 444/450\n",
            "3/3 [==============================] - 0s 34ms/step - loss: 0.2286 - accuracy: 0.9875\n",
            "Epoch 445/450\n",
            "3/3 [==============================] - 0s 33ms/step - loss: 0.2291 - accuracy: 1.0000\n",
            "Epoch 446/450\n",
            "3/3 [==============================] - 0s 41ms/step - loss: 0.2291 - accuracy: 1.0000\n",
            "Epoch 447/450\n",
            "3/3 [==============================] - 0s 30ms/step - loss: 0.2277 - accuracy: 0.9875\n",
            "Epoch 448/450\n",
            "3/3 [==============================] - 0s 32ms/step - loss: 0.2263 - accuracy: 0.9750\n",
            "Epoch 449/450\n",
            "3/3 [==============================] - 0s 37ms/step - loss: 0.2285 - accuracy: 0.9875\n",
            "Epoch 450/450\n",
            "3/3 [==============================] - 0s 37ms/step - loss: 0.2243 - accuracy: 0.9875\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Evaluation Model Analysis**\n",
        "\n",
        "Setelah menjalankan pelatihan model dengan algoritma LSTM serta telah mengetahui hasil akurasi pada step terakhir. Maka, tahapan selanjutnya adalah menganalisa model dengan visualisasi plot akurasi dan loss untuk melihat hasil akurasi dari algoritma pelatihan model LSTM tersebut."
      ],
      "metadata": {
        "id": "BfQP5TaPkGzB"
      },
      "id": "BfQP5TaPkGzB"
    },
    {
      "cell_type": "code",
      "source": [
        "# Plotting model Accuracy and Loss (Visualisasi Plot Hasil Akurasi dan Loss)\n",
        "# Plot Akurasi\n",
        "plt.figure(figsize=(14, 5))\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.plot(train.history['accuracy'], label='Training Set Accuracy')\n",
        "plt.legend(loc='lower right')\n",
        "plt.title('Accuracy')\n",
        "# Plot Loss\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.plot(train.history['loss'], label='Training Set Loss')\n",
        "plt.legend(loc='upper right')\n",
        "plt.title('Loss')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 358
        },
        "id": "FEz3P5djksfa",
        "outputId": "7b669f96-f95b-4d61-e4c2-dfa37b01bc35"
      },
      "id": "FEz3P5djksfa",
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Terlihat bahwa model pelatihan chatbot dengan algoritma LSTM menghasilkan model yang baik dan tidak terjadi overfitting atau underfitting. Sehingga, model ini layak dilakukan pengujian dan evaluasi model chatbot yang diperoleh."
      ],
      "metadata": {
        "id": "odsh6gL8CAfE"
      },
      "id": "odsh6gL8CAfE"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Testing Chatbot**\n",
        "\n",
        "Setelah mengetahui hasil dari akurasi dan loss pada model yang telah ditetapkan dengan LSTM. Maka, tahapan selanjutnya adalah menguji atau testing pada chatbot yang telah dilatih sebelumnya dan melihat apakah sesuai atau tidak pada saat kita masukan teks kalimat pertanyaannya.\n",
        "\n",
        "Pada pengujian ini menggunakan metode input atau masukan sesuai dengan kalimat pertanyaan yang dimasukkan."
      ],
      "metadata": {
        "id": "WcOYpQfuln4T"
      },
      "id": "WcOYpQfuln4T"
    },
    {
      "cell_type": "code",
      "source": [
        "# Membuat Input Chat\n",
        "while True:\n",
        "  texts_p = []\n",
        "  prediction_input = input('👨‍🦰 Kamu : ')\n",
        "\n",
        "  # Menghapus punktuasi atau tanda baca dan konversi ke huruf kecil\n",
        "  prediction_input = [letters.lower() for letters in prediction_input if letters not in string.punctuation]\n",
        "  prediction_input = ''.join(prediction_input)\n",
        "  texts_p.append(prediction_input)\n",
        "\n",
        "  # Melakukan Tokenisasi dan Padding pada data teks\n",
        "  prediction_input = tokenizer.texts_to_sequences(texts_p)\n",
        "  # Konversi data teks menjadi array\n",
        "  prediction_input = np.array(prediction_input).reshape(-1)\n",
        "  prediction_input = pad_sequences([prediction_input],input_shape)\n",
        "\n",
        "  # Mendapatkan hasil prediksi keluaran pada model\n",
        "  output = model.predict(prediction_input)\n",
        "  output = output.argmax()\n",
        "\n",
        "  # Menemukan respon sesuai data tag dan memainkan suara bot\n",
        "  response_tag = le.inverse_transform([output])[0]\n",
        "  # Bot akan melakukan random jawaban percakapan dari hasil pertanyaan\n",
        "  print(\"🤖 KadekBot : \", random.choice(responses[response_tag]))\n",
        "  # Tambahkan suara bot dengan Google Text to Speech\n",
        "  tts = gTTS(random.choice(responses[response_tag]), lang='id')\n",
        "  # Simpan model voice bot ke dalam Google Drive dengan format .wav\n",
        "  tts.save('KadekBot.wav')\n",
        "  # Atur waktu jeda sampai 8 detik\n",
        "  time.sleep(0.08)\n",
        "  # Ambil file model yang telah disimpan sebelumnya\n",
        "  ipd.display(ipd.Audio('/content/KadekBot.wav', autoplay=False))\n",
        "  print(\"=\"*60 + \"\\n\")\n",
        "  # Tambahkan respon 'goodbye' agar bot bisa berhenti melakukan percakapan\n",
        "  if response_tag == \"goodbye\":\n",
        "    break"
      ],
      "metadata": {
        "id": "fao4rG4rlh1D",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1377336c-d420-4a48-8e90-250061057642"
      },
      "id": "fao4rG4rlh1D",
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "👨‍🦰 Kamu : halo\n",
            "1/1 [==============================] - 0s 360ms/step\n",
            "🤖 KadekBot :  Halo! Saya Kadekbot, salam kenal ya! Mau tau tentang kampus merdeka, kan?\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : apa itu kampus merdeka?\n",
            "1/1 [==============================] - 0s 33ms/step\n",
            "🤖 KadekBot :  Kampus Merdeka merupakan kebijakan Menteri Pendidikan dan Kebudayaan Nadiem Makarim yang membebaskan mahasiswa untuk mengikuti kegiatan di luar program studinya selama 1 semester atau setara 20 sks dan paling lama 2 semester atau setara 40 sks.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : apa itu studi independen?\n",
            "1/1 [==============================] - 0s 39ms/step\n",
            "🤖 KadekBot :  Salah satu program Kampus Merdeka Kemendikbud yang bertujuan untuk mewujudkan gagasan mahasiswa dalam mengembangkan diri melalui aktivitas di luar perkuliahan dan menambah kompetensi spesifik serta praktis yang akan digunakan dalam dunia industri\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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D3Zvht7eOwzxPdp7+LXab0//NExEQR2WKsANYMlR9360o06iyETBuqcJkIY4bWWLcsnXpJJSP/tcLdk1YYlHOuoG5lncfoV45f/8yiuv0ED+426IOEtZgpcuROKgTLTDkYWHwa9lbZqe3V3n3Wb0GB//NExE8SCVqsAKYOlXOW8sWZAdpMriRsiOQApEtOimOgBa4sJcJ9AnBIhzWZFlk4f9FvR/l+hvmelRMFd4fFQ+KyjSZpZcVCc/s+tFv///rVa5X1ynEQgPmkePLQEcPV//NExFkSUWKwAMTKlCT6vfUtvnCbWPvuQyPIIfkT6sDQ3UtwtYWL8Z53//Lv/9Dej/b7fLKWwMCDAUMpWNAWWf7fmq0mYPfXgIQCzf+gMGb+YjIog9sQua7m+ksbjL5y//NExGIRcU6kAM4ElNZSlW1gtCyFt0HQYVA2es26lXlkqdt//4NQ3XEqNkFXEsqd////93ZxEjPgDUsaCAQKZBN58Y7mWgQjY2j8jgMXNSPg0kODTTnelNPL5bO42Y65//NExG8RaJqIANYwTC0AYJiRl4VEutJCV7yvTo//cj///+3R9f//6TM4HTHuDx5dTSIyjLIETQ0TjEAAwEKpiGCpEGRQMg0CyRhQCQwBCvl5OJUSYiIaAgqKyOiaSqed//NExHwRAJpoAVxIALjMTtbX75uh0HMJ7c+ln9f/WoJ1dZOLvZ3GAPdP5Fe1OXzmcU6j8W/TlMmrfPL66v85etw2wn4n5ffrPsn/6m91ZSiqwYYSd4qSRS+zisRWAUGh//NExIseGRJcAZ1IAZfLYqk3Nmp80TKR5QKC0QYYAMANlY7iLDCaTSOSyeAgA8HwRxrBKJRsQxSWnHj/dbGaUyjLz+nNsZ739uPMv3vqd++6e+X72ttzLZXW+z67Hw+///NExGUg8uqkAZlYAf6v91/EzzPLOe+/j/v//p/+/+XH2tVl1mf70uCRbCWct50z9BxgOV/6ld5UoB6zTN95Yq653sqlvfnMFyjvaMjniaoXBYhXWo+QpR+yTn/4+f9a//NExDQSmSqwAdhIALwlKqRnWAXYC59Zy1JRb70u7v////0qqZd1BKNpmBB2ONSJAkpfOXX6Bev+YVK9u8sPnk/ONr8ovo+YEMD46VxWCACyE4fujp5PIj+WWhRwMXoC//NExDwRKVa0AMMGlK+YtqtbFS/fTVdZMAYBoaj4rUBkxbxXfAQGTf+xurb/fwklHb+sEfrv/WmQFYy3z0S7/7Ob/9mYhe5ys9vaBYjfnmmWQESsBzGp/qZ9LIR1pW8n//NExEoR4Va4AJvSlQAEx7mAxwJ5eJNwBchmb98bESgVpSQwo+t+ymB/3t6OR3j8ifBQLhEj2Fi/9jzK96FXubFg6Wt6Yk+/pUS+Ie36sfVxyNpttqMQg5NqukUQ9Qqb//NExFUSMcK8AGvQlfWVSg6Inp8gjI8Jr/K6LklM6pFBYoqJjenp+qgj5RFX8SZ9Sjl6CQu51iQGc5WxJmR9neWIKfSRP/6h6db/03AtQjRwQosRwG2Vlr5gMgZaMruz//NExF8SAZq8AIvKlKAZwGtgp8ncFOFzW28NZbUbG/8GKJ9Qz/f6G+rVRyqJsU+oOqUFf/MS0RPd//0qfmIynN9UyiCMibZrkpiS6mRsVpqaXVnKD0QLNW4g2yQonpnN//NExGoRWU6sAHvElO3jWmWg4a7jvCi6VhzS1jHaPqDX5yot/tDhMtPDH//Y/fmWLLUqt2qOip10GLwD1B16d4I4Q8gZq5XlkSwAtx2TVoDkC7Ud1BQFbqLivxpdHDj+//NExHcSgK6MAN4wTIf/1BUToK/rNoB0chvd9nfqq3j7UWBRiMbsycwf8oY0lPHmnioaSnu37sOCKAsKTIk4ToyABcRE+o+bG5O+ou8seo5Hfou9S9ly//KlVGk//p/V//NExIAQeMaMANSKcOg+hgDKk6EhEKzOJD3xmTLMh+SuCrCUrDCnoPL4EqCOl2JCZh1HEolkuV4NUYBBlyHxorBSW7VtKss7bXp3gFQNf+Szv///t6Uz+UObTjDxoykY//NExJEPwKaIANYgTDAwgysuAoiJCqXwXqBCpHini3FyOYL4lr1Q4qdHQEjtOkV0u7MiJUnQoFawER01nXKZ+SPf0///26f+s6+VPyZOpsqZym7DUwonO3Z0AlQMCp1C//NExKUR8Mp4ANPGcB6pLoVUckeiH1RMKxr3LQqykgglppZdSJVvrijd08R07bsWi7UHhukJqZuPWzMRpfyl4H2LN+p2co2jkmWlwYoO0Lp4ng7Rgy+SQxSWHd7jgLIb//NExLASAIpIANvYTABIMShgCWAdz7YVILAYcY5CJQexTLS4iTP5sibso0NlyGZMgh/0Tdb2Ug5qaIvnCkj/+o0Psmt6LoGBsbJsSaVd2MP//RN0XYuFw0TMzdlIZstS//NExLsPsC4oAVkQAAlMi1kVufJqjtJXsxJqpmwvF5IdrTgVaUaQgg+W2mkAgS3Zdb3BDcFcMFK3YzThQ5oLYJIXhyixoDASuNWnklV7zVq9se2/3DjxN52/V7XbESjA//NExM8g6yqcAY9oAKCXEe0CJeBr4n/+qXv9Y+M+lc6j63je8+/h27zPx4dLRNipomA9Vf/+tCd1dfx/CnR0N0Xkr53pEBLtjeWVX42FkjKDb2/jXbkQwzssh+XwYhov//NExJ4d2hKsAdh4AGzt5R4GFLFis1YlKbiIL3W62VRrD/T37+IP7O65vVSmz/OVq6O7MBcHsEeXYcAQOmYF5wWLLar7HDtemcWf97sHnbi69Jd7rWo9yxmOyz6rKwMT//NExHkgajaoAMZYuC/m3fawXz+7Wscudsp7B9b3Yaq9EaUiwuxyfCq5pk9Vrw7NAcE51DS/PBjOHqsawX2aMDMxCeqYg0Q+1TWPwFIct87cq41qsrd9az2yNv708Qq3//NExEogWh6kAM6emK3YTTVL6BHjjumhPtxW6JS+pWpUxNQo+1fSLnEaHF1v+T/Gvm2vGiafxbzDQXebJhSitV4izr1VbWUAzsDsDqlLMQgUzS5WjQVCljlqvK1KyvtH//NExBsXEhKsAJYOmC+Nw2FxgEFqxKcEtVMIPzq4y19YRll+9b7//9N8df0/OzrGO6DYRROCCMa8dP1MLua1TCc9v9e72PmknsIpUj/6Ve2cqsSLB4SYnzD0qj7kKmbb//NExBESGW6kAM4ElHrbYhElatTsddWQhxrVK1mHU9S6MC5ZY1fy7/P+z//m+rev0/+6GzClYMxUBPGFTH/qDjGiIfLKSvpK16RmDCB0wuySX25RDSfX8nSZAUgJ/NEj//NExBsSGZKMANzElKLwBbgLCNGRNSiJKrolX1GKuhH9H+K11+X6v/9+aM6P/HoKAQ5Pf/0zl3clPTUIKMgbXKACpsMwPc6fjvzTLxbXYRPxAoTlBgguAVzFlvgQjdVO//NExCUQMJaEANPeTD41BO1B0MCk/TuxTeimgcxhtixl3/1LR////6E7C/LUmRBQQZpbAACMxBlQKZjDIAQFGnSqlQTMTUpiWsLifwtw/kSocvZGYkiJcGi0GgKC3skh//NExDcRUH5oANveSEPFToilZW3qJf/f///llTXZAzNDNKCCh3MoGTByAVB1bGXp+qsgeHaZ2Xie9iL0wiLBIOnqBSG2sFo2trdOv9lykevaz9rn92/+mn0+/N0qahJG//NExEQQGFY0AVsQAK2zbY04FDv/bl4wDGwoP/nbDjIxQG5XZMEYgMxgGge6Fg2sMXg2LDU/rd8GxsmiwKQEef/hiQkS+JIGNxOf/+ITjTHMAGeKORQcX//4lAiA5AzB//NExFYhmypcAZuYAFBcZumWv///0i4JTH0I8LwswUoJsDFAnAQE/////xOBfGQWbiCgpSKDFBjvEEyDk/XNpMVeilyWHhw4EE3zvPR4ob6x32ICXnL5gXiIGkL+ZgAa//NExCIacWqwAZloAB5m5qgmE7IZkZh/BZsUlKMTRlOivZsxQdaFqWh7WW6SFloIJI1rma5cM7iMBKuGnMcC4uUGgUMiVaaU+0YZEgAFN8H1C534ldZZdxbiiqflCQzy//NExAsRoYqsAdmAALkzNK7IiFJip7fKsphkiBpsavEyGh7IGhmbOm6IuAihqn1N+h+v+n+YNXebE+prZ1vqPag9aKO0tZXehdZ/vVC/5xV7qYONaq0zSRo2P7+7To5W//NExBcVycaoANYOlHHm8c0/2a2O41fmS5zk0tbmUohicy/YxW+Vb549+PGo7sUG4CnSqIxu3c35Uy18XEgyKgo9QjNqJhwZ//V9n/QqpT47YIqGMq4atpiYhTlr40cp//NExBIWyva4AHlKuU7PDpW6kDoYQ46iO9+n////NVu3+m3/e77q33QlZ0IynnPkIHByB8PuIMgcJEw+LnOdJyEId2nD4cDgIJnFznOHzEV6KJmcdgxVTww4CiO11/////NExAkR2x64ABAQvP/H///X/yvP/+2vCzS9XTRYsLFXKkjRXWrIOGxKqHNUNprEEJRws4eipR5QhEojipTg1VxogOaKj1lBDMYZSlA7///////y//LX///fr+3L/z/9//NExBQRyxKoAChKuf1e7OZKOQugcR3OhXZnUPkOKibMkgHGHOImFVHAwgLnKQKOLCbiJ4kIEFRouAYTDVCwnVVgL//////1////////////5j//5uuZf/+YTquDSlpD//NExB8Sax60AAhQvDOEAXFUMMHyiS6MR4qJ0dIKZ5FBgOhNJAgoktNliCQMOOOlKGjjh0Hqx7phk8RdhxlOrNW7/dMYx+UzgP6kikf/w////9X+vR+b/tzUNlN8patt//NExCgRwrakAHhEuYYCZHKhiiUQ3qxkeYpS0LUKVHKGQck+U018U3yQ3YtkTkyyqoEe5AeUM7zxpsdwP0QKPXUetLbeJxEqQvx+vAxCcsW56Pbfe8z3g8hRz9irbt36//NExDQRkKaIANPeTK6ir33gM2Uf//69h5jnCJxQquqQV6kPl7DSfYMBH7kEhQzKb5retwbbxy1ZYPavyiceAWrjy5p4LX/uvTdqZD+7JSh2ZcPP/yDwkHm/WsJPmByT//NExEAR0KaMAN5wTD//1SVSZmbq3h+DhjkOtJqd95Wh2ZqseAiCFwguKvblBvFLvxpwHF/HXAagfjrUiglZ/4e776i/f7+fyNoEACuRQAQsP163y79ni6JOr0AHQLaC//NExEsRMVKwANPElNEO+G8nHPDlgTi0pSheJ6zQQtVRRHCZJImYm8hDZM+eHet1KIPxqc5ujP0O/CQdScOCZDIBPOQOiBgHPLGPr9Jo8uqt8xxIAByYj9sQ4B8lbuGu//NExFkSEVLAAJwKlIGaLTF8OAqvukE3lDm0z9Q6pDbVw5Q5GE9iXOX9wETopuX0MmpjO84UBdhQUCcUMKfoqytdbIMKGEICZPNluK4AQHCUanAIF355CLF5+TuLcxZD//NExGMRKV68AHvElHuIABHPFAcACCCI8vacQlf6fx1PSc6QiPWQOOi54ZrCFMVY7LodpZNr7BD4uc1Kgdsu8nUy6e27wAg18W37rgGA1mpComakrDEmzgGkRYNSQoWV//NExHERMUa0AHsQcIzWQ9S9mpbWHwBEiQwoKAiQwlXkU2kF+W2PzS/LMg5ujQdTGEA7OD2czEJ1kLRXQYXBCD0jiYVBqzlS4qQKskuqpF/FgxFHBxvw3GnmiSzN7C9V//NExH8SaUqoAMJGlcxfemaodNmokv1LKbWxgIyakGjKJS3h1UDLMCY0/Q6e91qP//pqMzAFFQGMHBOMaBeAauGmo4mFYBq6MBgiU+1eXQABggEgzdmXvQgEnN00Ze6i//NExIgWkVZoAOPGlL/Sw/L70cWSnWcuWqb0cKoHGIHcVY4KjBe0gHyQDY1rLVwyBcUe6plNZXdc5UhsGKsexVdl9CixlYtfUZoSPDiUoMSTWlcwEbM1Zk0H6bFFzIhQ//NExIAaYMJYAV1gAGjNnVaHbAAAH1Kqls0RqASIDR9mW6YC5gNOK0DnqdfbYcwphxgWJgHX+g9sEaA3LDBYyIhcd//+mcLhPnCCCd//9+RwuAW8ZQXAOoQUHAV////y//NExGkiCyqEAZuQAGyJlQ3kHL5uRQxJ8cH////+Ym600y+TZuTZPm6BME5VqAU2CRFLTF2EYDWUAIJ2xhBwHhTxk6oX4Zs7LU4q1dKlrXDOvuU0GPiekjpt226hv50///NExDMfIdq0AZl4ANpX45MMwmux/KVV3jw4xzkYORQNa20iP7Tq7cn73N4fqfLtTXpJo2TXPdwl+c615ImLeu76mvExTOIe40aGhJKOZv+37NNn9n6Vs6ymn/Iuo1Hr//NExAkTkba4AdloAO8RgyLcnqbKgc/X9zgbv/uZPdZ/yd1lfmKFTJDvOJMiDyPZTlwrDOjQRHKfUgdJoijYzYujCKNbEyrUn5p7P0Sx1jNm6pW7+6y+QFhZl1l6wLSt//NExA0VWbK0AMqelNy/QgAPcqGnQQBvV+YNW0JHzxnF/yxwtbwpC4xcvIgs6azeRxMreW00z4VV5WNNqHdKMEf+lIVvm9v/TUbfo8limS52H6he3QqVXsMFkAsu5bYQ//NExAoQsVK0AMHelGyEUj/PYARLMC4t1PI+S6r0Vt2f/Fbf5bodNw0wUK1WIwluZsxYpbWV7GjKF97+M9cTb5iWwEFUJjqIV8zBdjxl6GXSxnIoWZgMIFyITFWdLAk+//NExBoROT6QAMpScDlbGMvLf//XvP7yP/8fsYyupIia0iaMVjQhJaRNLEzRUyi0SrcVV538ry00OcOZOi1IBAgAOmMCICEVAS2Ks69H6gFdrEX9dmHbW/q2dAVwSCrl//NExCgROGJIAVsQAAK1PoJHtcsVMrCR6HaAoa9rp70/TU6St7fV1//SMERTsGFN1G3V7QJH7cuo37x5lqGH4U6TJIhVB9GWkutnXKYbYO8AQ9ns1KEwB2AkBgOShd1V//NExDYdmyI4AZloAVlqBYFo5BeGWPRmXb6uSjoqbZv1O727nDQlE86fN1Pqf6TLW7ehoUGc3WmbqQPepdPq/e7V2v6p5NM3Wmbsmb01Q9zYj+YBZKesQUhC/dus33Tm//NExBIWoUq0AY9gAG+6Y1PJq/AeR346mZtLlzyt7NLjr45jYabM1db/gcqbNPz1aLm+maUmUdniiRYhO8yecZSJ7FL/SSG1XESKzP/IVBgPw/xR4iXe/+JCpkSYzS1q//NExAoRyVK8AdhAAGS/Yo/09r0q5DZ5uoqSpj+JQTWupI/yBevtgo1NInDUysmiNfyUbz4OLzwIZV9SM2Tm+UdUdb1E9gYkENSq7sLLCi9RmFlp2vVwkJi21jIBXNre//NExBURwWa8AIPOlGCTTX18tH1u56NOc4oJ3Oc1wBd6CVvjXqg1MMmmhM7MhUY7ldZHPoUHs9RgJoCF3m4B1qKIIfE+pVnA/Ql2rWBGVWougSDdmWQwXKqnMCdUpSAt//NExCEROWK8AJQKlASSaLsQUhWWgUP8Rbw96C2yjUctXAqSuNS5taDVT5Bn3NjVUY9d1yaMkWr3s8HAXFrPsMfYDCqvtdmsP22bVL8oo/tjdvjSkOKN5oTAZTkVLsja//NExC8RoU6wAMPElBlaxfp2Upc4IBKIQkHaJ1W3fuxWx5iylTmGROfCBSBI85kmorbYUklDx6fWfAqRejiXgRPI2T2tu+tUauokMLEsQoCwaiXSURB38rHuDR53/zsl//NExDsQgMqQAMsGcBKCqw0VOh0zdg7JAwQ8xQcwhE1T00QNQFTEAjBYdGBNkFIcyHIcfpOXl8WtBhSXxmm0OJmmtWJjFQHBYOQF//u///3/rd/qNlETBTDVy19ejF4l//NExEwQAMZMANPQcA9lPa5lnjczUJlKaik64VVa9RMcKmE45Q175hwxWaoOgmuIDh7esOwgRaQbWx9LhTMKpW5C3y1dgvCHGDBVI4TxGiTngyFOXO+Cphxv//LWnkv4//NExF8ScEokAVoQABry4IQADAj/C4QXCHrgPCfvwMETA3JcD6swMMsAKcf/gbIcAaTAOPgZ8CAsADjP/8MKDLmxPqNC5//+dJ8+aSZIsLgE6f///lkiZPsmRMoFQiBm//NExGgfsypMAZigAJkX/////yOHALATZ8kyAFQhBz0jIqF9hVFSRCGBQ0olVFgEYS7euPWqV77ZwpHiSNzEyLh5AzUPxMHMVjmKaaZoLMNgWAc8umR8lgvRNLiy6Ykg//NExDwgCqasAZhoAUmWFIyNzy02UucTQTTo/UpOedFkDVSKLLW6mrSWt02utN1Uk1rNakVu/f63R7a7MpmQT/Utvo3czfzT1obAo7/4tiDSqt/rIsAQCvzS7YwRQR+k//NExA4R2bbAAdhAAfyadSRf+EQq2eZWLbXAOCK27mD6FAaBo7UXFhWG0mv6/qeuKaaRF2gPJiHuP4/7/4/vT4zzJ1rdtnXn7rCnHW7ckY4xcU9uaVsKHZf70PLzOs5D//NExBkRqUq4AMYElTa/hxmFLqbkbiRbndRt1b3/Uxx5QvcraP0VuY2QWAjEYcz6RUjv++0JOkF67+rk5bcAyMwywhrbsKVjwYSDU7kjoAx44OFL7MGpuurdh0hAESb7//NExCUSgVqgANYElAZCCBoazty++sVy/K7S2f/v//lb//b/5aCldQonp5BhUZ/kjpGnj7xCIFNV4TSg1yozDBhQPNzWUL+h7AI8Vfr3ApxXU/WghPGzzl2c3I0Vvp99//NExC4Q8I6MAN5wTBL7P8uVIDv9BCIlg41f/+2LW+QD1a6ixfwu+btUgqXX5F3TGRu3v5LPOiiDegc5a4Hak4gTwfwrqx1mvL3U/W/Be3P527dG6+//fUd99njaQIwi//NExD0RgY6MANyElO//9dd6CxICFca1CrICMSvrscZ6FhT6x6hQQA5kduVGnyPV6nXZOYbm1ntcj9+ShcBAICBUBcG5+HYfw7EV83+lf3+ifvy8Cjijv68ufcc/Rdc7//NExEoR6TKoANYQcCw0qHiW6ldaeeek7Fr2zQqd/5P+b6lm1bMFliwq0UT59Z6no87etBh4+L6nnNqdxxdBwupp4j6mD7a+f7eXHnB81SreNA7ZhI6IbyQ80VM93qFI//NExFURGZK4AMPOlAKYOaPrL3OswWfF9MsX/1n9iVfCR1wCgoSiwMAku5EjmvMt6re1Ja6Po1GiVQVO/K1B1OHaqyp6SEFGRJcBQFANtIwFEqf11N+W8OJPFUWydMLc//NExGMRIUasANPMcGmtury6aqUdJnS9+rcvj8N7f//S9D8G+oTxmoDWv///VIUmSAOBWqr39fpPE6WnDHFWuEDIIY8DNAvsA6P++ARS9lh9IBZzgpGj9/t01UBo3PWc//NExHERUeaMAONEmKZI+p8KvK//a9IoUHzrkOU2///8Uu20CofecI0oClIhgDAIa+kJmEUgILr3RvMBBVNWN5vXD34bY01Lnajsxn9ikHLH7f/niwkKiKvVKuhy3/5G//NExH4RqMaMANrOcJw7y3///6Q1wqWHGnnqlTIgMDEnzgcrpnve4KUk1MZowRBUSDkxmDUuyYriWRAekbG19NUd6WALAmHIUD8HwW4WBdYiByUXKiHR5yCwFjlkiynL//NExIoRUMaEAVw4ACzle3+H4WmKHpLU8/adOa094+iz63+NU+YuJRq7u6uqmz7e/t+Oxd/T/L4+soHTJf1pT3RHR2Ud/bXv6XsFVvVrVuC3jum2iry+vUzwwNYCFqGL//NExJcgceJgAZ1AAbzV53Iex/ZD0zDJC5oxh06p2+LYyCQWenKSsOVpImVsY4d47C1hwiFIAQfxII6A7CYT7YblNk03aarkKA0YHE1mP6l7GMPv3yyZhrVlN1sn///+//NExGghuuqsAZlYAJs7WNhzj039//1/vvtlbGG5u/3XudF1pdwe2hYtWCSM3oBVKKRwFYdaVQGWDwHUpWxWzn3v/QUPP+SRmzbd1rf/j//MLf93v/04/Hwz1rWhUqlW//NExDQbMb6gAdp4ANl2A+xewmXnCcyzVtB9oTE04JoyZaZT+t/tVdfVotfhgj51RsQ17fDw6gQ/Hf+/6cWMrdqnXoWqPnKilSJjMce0yCGnmEKADJZdjuhL8KC7hQXc//NExBoX0bqgANHelK+z8fLcfJfk383rb0gUOrfiFGTWjYaBbAynNsUBgqbUWQ5DiiagPcU19Rc5zdx1/JGvm8JtiQvAPwLU/ilbf0//MLR/YqoyAEIaCobV4KJgSNOE//NExA0Vma6YAMlSlPxlPY1ZoGxIDboHhbMj0N/+6xz/x31fpqJCRLsIhCZCxohFTyKbORWT2kSLYxhtS2P/rf/X62hUBAYk86dQVsXWn//2LmdOaqJVNMhwycMfAC7J//NExAkRESpoANlEcIaVBB8WZZQXiY0pdXEAMtYk6Grv3Vv7/X1bo8yiTI7GNzBhQaLCUgHQ0eSRbVWWJAUke7e3qt//6h/61RBITxCAgt4YJDSeCZQlAMpdXcdD6xK0//NExBcR0D4oANPYBAFyWnQ7FoVsx9zyC3oF3JQPfDQlL2pRNoVLtWpKJZzJPGOsTpQNYNqYwAT7rGV9QxUXBQIEtbBkTIQoIYDZsOgQDAGm0q4PUntLkZhZwJ0JcgJx//NExCIQiCIsANsEAHdNJQwXGUKLHElNaBVBHjLmDrXUtoSy92hR6YVtLm6Uqge5BpR32AqB089qoLj2d+KgVIFRJj9oxExeISECFbH0OSiMqF1EXOlXSyCTKLWtFJYQ//NExDIP0CYsAVoYANKastZa+wQbjVLT6FIqMLQLMJBMMbgnN6ThMigjOoBRMRAUQAGRgUkw4gwGSYiX4iiIwKAAwiDtgI0yYPCFiJCwBoIfGOlBaZoPJXNSmVCqj6bm//NExEUhQwJYAZ2AAUtNTLRZNaH0WeylMgkaX7aRy6CmdaL2b/qem3UujQegrqQqpv01IPWnfRWhezWobbamtb7UGd02X60lmKXlAhQywAg1pAJEnUECZWBhwmRPqJAk//NExBMWGHZoAZx4AIiWkyYgAyahgUKOQIgzL0EjL0ablyauTi9huo9hw08Ca3uc0g9jnObEmhd9knVUUCTFWJTubZopRWBhbZdY4outP7nWQLUy4BMuyQxMMmsB5MHp//NExA0UmyJ8AZtoAbRHSYHgpxQVGINMyvVoECABsxvPGCZ43HuU+/hIx5uPf/z7Eo3/9RgaIFxv/+pk1N///0NC/////7q9//////VdPN7F9IpawAUjgVYzY0LasWDv//NExA0VMJqoAZl4AARPlOitjc9kQ7wi4cob0PWjxFMRpHFmKRM+eaQmJjndeQMg65RJghWkno8nP72rB448u8+GVAzdeEe+8c5H3fYsuIGT3hL8XpbnzGAlMgJqW/is//NExAsSmT6oAdk4ANQPGgq0mG72GdWVMRa/ljmzEtqs4CwCDAmEoMgvEsueqKTP9////9T3cgVCwKCQXa8alrQuBxVDD9BD///+olXmsdXY9EwPGyeV4S14gqACizLc//NExBMSqVKwAMvElemHxvDzQyLbJPQ4iXk4eUjYZFcoi4IRW+rVj01miv+hE9OnOc4aIBqOLDohahcrp27oQtUM3fVSlUU/v3G5mqYTeBZmx9okdB53/22n6ajn/iV6//NExBsQUUa0AMPaccKM/RNRpFYZamSZzpIGnZF0P2b0qL+k543WFBUT/5N8LnGgp9W6KjOCVhpabjhscNPQ5zi7qob/nXQ3iXLW3sJtbDSJ0qrYrWErlFHa/1QgFAat//NExCwSCMacAMvYcGtq6OJ4Gjyyx4jEXOnp0SmsO/+0Okv0yqP///XVNWmzdBUyk+M1CDAhcMCAMHAECMBBlqsieYibJUKEKgkTXCUxSz4pPjUtnMme8JGkSwCYmEsI//NExDYRYMpYANpMcLyQdzuqRuO9X/6n/////pUwEYVCISIu+LpTIWOVikM/ozQUQJF2kg4qLNS9BGzNPWFVHK0iAnPznQ4HWDwBWGLb+5NwfqulojAChdzXohAkIVw1//NExEMSMEIoANYGJEXvc1DmJTnANTFMFi0EVffWBctZGDTNERoj3q8taIQu7la/nxmbSiERaKMcK2LBKfFcu1RuZc5w17Km1pqIjCBOsXralLgyA3PR3peiYTtGVyLW//NExE0R8PIoANhEcHklMWAxZRBZifofU+jZhxxZJo86UCLFiq9m4KxdrWQgzCHjKnbdDx5pbHJSfnWJstFUV4Da5Jik4s5hrmjotvOBpAcoqlnfuU7+WdM5xzolP2HJ//NExFgPABosAVoQAAPvRE/9q6FKuaLv/zB8jxyOcQC/r//2UuJeYsepP///Xf8U7xaVX3////o0dilIiXUU92VMGjI/////9Ke4m0l4q/auiaPWpGODqlosUSqBilAh//NExG8ZiyKcAZlAAWFzDnEREvC5dHU/c39L/3/4/9/9J/0WrggRBaGDsAcHnFcsTHSSwNBLB1PdbaVX91/vV8lsaj///+j/+qrHD/unmLacy0VCphRO1zJPCYP4DN1f//NExFsREbK0AdRAAKj36i/Un0mFuK4IZhOToBKFskeSCIZ1MCYXMVjBr6EvlvU7xUdmnFsv////q//q/f/5qBRXHuTMTmDfS/mTAJQKCDRrLX0x6r5038o9ZmU11DYA//NExGkRQcK0AMFUlMVG4B2cqYOgTdutw107x13uXFx+GahdXzS3+vXXK/NsK6fdUZbimjPqXbm+7pj3vjVvGqqgPQy7Vpu556TBlEqujpUos+7uFqqLvLr1tTwzwgNP//NExHcTacK4AMtWlDwt07wFtHOid+gQyUx5ZzlrSd7vTRLaZz9HlrOoKBce+fGcXtVN6vejtjs8eZ4lIUbFGjdL4b1u0O8VSadzRnjr/O5/jecxfJjDJ8W3LJrFLRkt//NExHwgkiqkAM4emGPe6r//+pW9hnNKom4nSuaxmVByILc+oMjxJJAM9DswWZaler2GMBFYFzsyxTBs/12ECBeb80tRYIvU71nLrZHWta/kqt4/81ay/+xq/jMtHUUz//NExEwiMjqcANYYuMIQ7XgaLABgbSSh6IJrjTJOOFd4XxJOoq0LprL1mj22TrH7P1yZbstxxGSE7Wraq3fnn6BscNBO9n1rV6Wg1cgsqiDNY3qldJJRwXGZ7l1EEmzG//NExBYXmgqYANYEmC5aggL4kF6pBSAhilrUBQtoONnN0mdS+znzK1z+cy1//rn/Vfv7f+isaGNq4JDHjKFlDalIX1r2eilMgYHYDYbEpY3EqE//rQqGK9p5DASk70mJ//NExAoSGJ6UAN4gTILeyf2Wwt2de6CsNS9KkEBgGLYVyZYCsO1kkiYuusySrckCuX8TWZPbTEouGuAHp/Ej0iYlW9f/9utGZRHRtRoUmuQwYjimRCz8xyNigEBhX+YU//NExBQSGgKMANyEmCLGXUjYgIBbEMNi6TYkIeq5umXjVnW6T9T9H//t/uZ+n//9UX//9NDKUoZ///6NOJQC3f1qKDIUIasXOMppTMIB/FAHCAPW8YBgUXSUlDg4ABgU//NExB4SmI5sAV0wAASrC4uosrcu9jj/MQgJe1UkEUaqy9P3rdo9q2f+er/U/tT/9Vn/1PLanvx9dRZOGkI4ZmARpNOjTANHFQeH8GkQRaGYNCYkBy1z+J0yxRF3BCDo//NExCYZsyJ0AZxQAbBCFcFknUQYqkDqPiZHAjCQBYAQ7+shJzBXFvX/gVx8LAqDyn/8aEZc9///9GJHmf///+YYrrM///////ax7k4hg8t3bC0ZIDPPoXwLjndqDBmd//NExBIW4Wa4AZhoAA5Tqyw4rKqwuGinJQcIm5iG8PRBEeA1DvIoZRjCREFDyjsorc3UwsjUjp6S3ahTvWt7k9v03Z1WNSgo2u3jqLQg136/pJf/6f61naegozKJHV/K//NExAkSSVa0Adh4AYnOkOAyxmHbilLNZTjbnabufHBot6hryihe8VXNs0RLjhcc0jPt69dfNMW+d1/+cbx80hfUkN7TMkd7nEugukUqhqZrOiO1UlIYlMpyAokVTKRE//NExBIQYTawAMJQcf6wjS9wI26/Xln1LerBWI8OwNBHqWib+b5pf+/+puUGi8IYE3LbBbIiVW6v/jr/qnynKjoG6qxZNTRsLBBzZZdwAI2r1xJW9lZ/sZWu0vBJeUJI//NExCMSIUKkAMMMcKLmBW5OEqq6+58rf2/+dq1pY64Ski6pH7c8rPez//qwFv0+N0aaPVbLJiAMIzBv1hnRDBVAkioLRxrjSJEaXAKjKLUWRaKnCVRqGAgI6uFAWNQE//NExC0QEMZ4ANGGcAR7t/SS//9X//q2L/QywJD+EnoqNRwo1iQzTgxMblgwSJzGgnFCDQi6KCVHxfz8w9DI0aQ2zKXdJqzAaap9NaVb0WFn43ZvX+H5/7PUepkvbK1g//NExD8SIGYwAOYSKCkkOrZqsRTpeNoF2BGYIgjtQLALsxXKxZ64GRM9DRNLmTjBZulTN25Dts2Mc4q9V62mknYs0XxYu9CT7q61poQIE0aaJE3ZfSOSpK7F1b3s7Z20//NExEkQyDIoAVoQAKKov+Lv4xBuH/GLEw7366BxEHJJ/x3k8/R5ImkF/5ufJA7CwwAmH0Poef/zc3Pkw5R1NEnHkv/+2U9M+c1Sw81Jb//+s+97Kz5NPH64eXR///////NExFggmyqcAZhYAO9N7GMHfJoqSB0D44qNaJg9/////47z5MOU9M/U9/5ALoqpImpMTQPUosqZ5S6XidUCQVyvk/o4QW5D1rfLGf/vCnx1+RwZvy22XwQea8SZjjBK//NExCgRoLqwAdgwAE8/nChcLFgASLptbnHKPuKa+ryNXqX//3WALFETAirPmNMIgByA7QZVZYWYsGmabTwmAwtoAAdaouKr4cMzOHFAKrAYrjvKaJf9D0CDClEgYsIP//NExDQQATawANFGcWfez3L/XXTHA7CJ54c/J9AtGLwv1Ds4Iy6kIzA7n9DiV4EClu4lfs+u+ovLRAUFXQKxJM8UozD0DqIFnOQUTEUFh1ajiDC71tM+vrn2KVP1Jgl3//NExEcQ+T6oANDMcRjRx6IqEUlKnRWmnzUlEJlyjQHESsZFbLVst+XUqeOdVUh2iINIrZWRQRbcETVSVQoWY54qyigoK6Kb/gx3hXEzsF9kAGMJus3zJjIYTQcQyAgh//NExFYQsUqUANFSlVY2WxUHiEerJgRiKWOG5TJ1k2J59vN9nR6zV1spkFRuVKnbUBGMYK/+/6Kf+d/9P29ClTMABWgl0YacJ44EmOgRDDkGHQRC30g0DAm7aqN2ke6W//NExGYRUPJkAOTEcK8NkWtyinz7tW5tgqNoV731zdZKihidPQ5Pt6K/ts/SW4IiuwXeS+VTs8uYubEe/K78Ya1xzm9Y4h98chWS5QGODtE0C8/TcuFw0JQxKZuM/5gX//NExHMP+FpcAVwAABk3jQSY8D45w4/5LnDQlCeS49x4B7EnHICQg7hPP+7NtpiwGwd5SWaDkc9/+9Prfsbm02Yd48yQN3NBg///2/UzegMOPUnHRhDxLjILSeVkunUw//NExIYhGyqUAZhoAMs4iAMZK3///4//5/rS645xeXIFKFEYcPPhGBqHQNAlEgNRgThRBGD2R1E6MaLgpEIaIg24NQ+7aWqH7udiW3/fuqXvq4qFu4W14gmpqZKp6aWn//NExFQa6xa8AcdAAThBGVMrfTCUxMhYmonHM8HEjOFuYUfQAm7hLAusgplEPCd+Y/n/U/zPpOe9FV2HMUVEDTDDOsrpEgCcL1PsWuJQESAQVQaLPy0fU/Wd9bj2p63Z//NExDsRKR7AAJHKcOKphsjTIMow7K1CtIogV4G5Nq3HSBcFj1GQ9D3WUX5mSBcavAYEjFMzLXHqBYNQy624b8pq9/VITC/haILV7DSpKo0cQZ//////+pyErec/KdL7//NExEkQ8SawAJtScAuvYtYwpo6YNaX7qLVEJzFS7iMDh5BBEEoFsIJQIsTItqCOpJ0WzjPObTTrCIxTh6okehjdD/u3lTKyDv////2qw1+7iBZKZK9f2yACQfXUWYHg//NExFgRgZakANSOlM/DpzdloEOBsWbmdQrwAKB4OIOiLUOAnG6Bu/U/oT531QTFznaFhxXd3I3VPs70iIgGCgqGP8oqbzEG2KWsyl5MrHV35lES/jre4yyfe9bpWkj+//NExGUSSZqsAMxKlIwxICwD0v43FBp/yb3/Ev/6f/tcfljUTUvD6RC+pufYsFz7UE675oDj1131mQFYRDZBMmFB9sQgJp1EpW+xBkL3v4uLctJJywCEFjQZz5kLWO8///NExG4RaT68AIYWcOV0G5z8+2tEpGadlImAu9R98Q4LsWgccNvRlbgWYtVu6IScGR5xRNAfSHj/K6Frmx86biMTf+6dUH1WqmIM/z76qpQp91ImxQ6knQ6zE0T1pJF9//NExHsRkUK8AIvgcCdai8eOMlCdhyASYUKrq8kl6eU/fwoSGbFJzDtPbXYxf6pegcsen1pXkhaMevgNs3+KREKx80bCzAIT1eeHvX0Wbf9lXHK4cqroaQSbH1K3Xxty//NExIcRgVK8AGvalL0tXPFDaaeUbxlrhGdANTvtezgklIxC9Qa6UrYda3EtZ3K8zX5olEznCCA0TEVHKB6J5a6/OzX8G1/w779rYuYmjYBf9VArAgxBX////+MVxdvH//NExJQRsb60AMPQlBd9Kg445IqV14JLTjDF/QfT27sMtad6nXIyIlLOqE9RrzaBNETgKIWVLgzQBNJ1T1+p6mzv8WKrUpdIgFCRhoSb///3psNKwiN+xBpxuLOisGP4//NExKASUUaYAMvWcChoYSSEuZMhSBDxY3B6/RjYi5VGwXu3p8/24KBIOsacXnu+ronb/0bpPNdj0IKDDGf61OK62IpVfohPD2FuJqsWOaIuYmIwpD0KNZCiM/zYpprs//NExKkSgL6QANYSTIYSwgjuBsrlUOA4OgqNkI+gPnxZ4yd/f86ShIJHgdI8nUHwmSU5wkTW1v/VspWYl/INNbVL3eh1YMwim0YS94uAaUjjOOzF0GrN22yEIK0vxjie//NExLIQ0T6QAMvOcBcHFQqSSARI///+ZKhgPPW9ZUGipNbHOF1iNslMxajrFumtG8rwgtDP3zeN1xDYB0EaGy4mB20Rg9p2lrJiPJKVVh1KF6q8YfBucPR+n+8Diif///NExMESIJ6IAH4YTP/UDCip0eLb5kBvkzjGjr6vZ+OVk2FV9kRDyTELVEp5uwnKJnsgZ4v8CalYM12UpvMhisqetZJpFKQb2SOinqLDyix3CKfzmFjf/+f/d/T0/oyp//NExMsRwIqMAMZeTCqcCIZVGWXRXHmK5GiBXoo84kT0hBuBGPJoTZZ//0KEbsRsATD2LXdf+WrsOERTBn6sEAGJe3G2gXB+zUjDcAQkNOVCVkVARpBskJRF4+criLne//NExNcREI6UAM5wTK82pC+R+rdH6FWgwJjRFxoUY1mfSVKxAWQiiAbpHICARIC8VDhEeJzZx2tjuiqL1K0yOyBlIOW2ac+5CKDQAmtPCLsPUjq2hkWxSxXxCn1ad4oo//NExOUXacKQANZKlMaaMgGRZIiIoWO5Kb//R+/sj6ERM8edq8isTCIKEBjXPJNaVQCrF///pXRF0h9FaIhPaG4BJmBrOk3GHPGSREd86XsEW72BuH0SaTGGKDtY3nDa//NExNoYUcKcANPKlMtx+Na3L5YnrbpP1ev1/bqyWv/79vTyv2Xlme0iua//////0rl0SaAqxZdxVTNAhCC0XrSEM6wQ2mRg4LrUTWTmLLL+Q2EK8ZTn35+jhSSFVP46//NExMsU6T6YANvUcKO+759P+q2sP6v9UKvW47ErqzoKu/7aI+d+S////5UqMHI3vqPLTgsOmgLZlRscC0GAj40MEAGkelDFqaCWmwFD7WZt+Y9bw7ys8qCYSe0s88jZ//NExMoUEsqMANtEuf2WiKzf/+VZ6P72fnUfsG3JMQkBvwNysZAnweA6TTjfJbjCGpfHaEVDg8OYSjFwS0eIxSd86bkmJePMOERoWI2hNvy+Pc3oRwlwyJI8bfyXN45z//NExMwR6NJ4AOPGcHqNRMh7GwnxfJ3/QmimL6cvk0ol0yuTiWb/83dBbrTcl3pnD5mQCQGSUxzCZD3Hw7//5Jm6d2sm7G6mx0GCJYkVJmC0CWSLxLGKicVsZ3G7HeuY//NExNcQKGo8AVsYAECzV0VNVOgKmVRI3LaXC6npB0t5WrN1V+RQySNRSIFseTI+YDnEqOYyKLTCjUktCrWgv2TR8wMNmSLpXe60DdP029BP1GdVU1NjhNoYKIAobnU5//NExOkjKyqcAZFoAFiWLut989PBVlKzsk41IkZaUB368EOgdYqRC4xhZdMhbnCFyy1Wxm1fK9vbzdMtWGEguUUHvCYis1ub/dh9aLv/9ye/srehz+a3nDptZQRgXDck//NExK8a8cKoAdmAAHqinJRVNbpWl41ZVZ1GrhVZ1DVP7f//Xd+mA7wDFn+d+RmJLGbCEwaWwAvlW0ALDku1Myyyz1B2EzMSbizkGFASYPYa8iY0/lu9kRASv//q1kQk//NExJYXMcaYANYOlP/u/xF///5Y91HaqjX9I+OWNNRjVUozkuMnJjFwhVF1BCQIdBa7VBWutdoq3JVLruNsrXJY2AEYPshUS9v+tzVHuvs//9unW5GWqf4d87/6ajqw//NExIwREJKAANYwTASCyhQdYVVaVyi9SWuVu9/WVzBbRjnoDKnIy4hllUF61Im6ZsioWLi5JwoHFXvq6bSsW0U9yBRk4cay5/NQ4TSLviyziwhToWMSY5OM4ovH88wE//NExJoREIpEAN4STAFYv/fmCHA4pe6mC2wHBDI+ykEAB4DqgKGBJP/KaQ4yUHB/+PQ5hUJwh44/7flUn5oZk+TH/9/IITgarIkOAT+MYLgEA//9f75w0HAOsd4pMPnH//NExKgRwFIsAVkAAHjHiUyuGR/////8NVkmUyDnzUZcd5dEJxS5RELil3GBhiHhSk8pVqBCiBwedfkXaN3t24xKGOKoLk4mAlGIkIEBcQNXcks+94VkPP/PbHzExPvc//NExLQfwypMAZqQAM656lRm/mbrmJz0x60xzUVErWft91alQ675lQ7VN/7q3rH1rP6nXnE6ddtvbB91nnXEtibP7OeJmNl+1zro+udWXe5H+s98MbsOvZ3osKgDPlBN//NExIgfwwKUAZpYAaoGwh4nyMGbMWDZPG6BopMHRQdT9OQmbuYnIZI1FGn3mG6VyGx223R8jq2NLqT/6P/9frrUuHEXfYvOpViUlM3bBSWmzrpKA9YCgTTqYvBC4CqC//NExFwQwI6YAdp4AOUR6cL4NaBUCUImSJ0MsOnSOly+p/T+f/////YEMEZmIRikhBDVCL93Xb///Tt11dffsPmcBWRG61V6SFEcEiy6U1kQQvAaiRY8akOCORGpYLbj//NExGwSCaKgANSElHBQanUxma9Zk/t6/////+UpjCysiKOFYKKU4wK3VNyOxK1oGbyT+SeckyDQLDovO2DcAi5E0SGlUi4A2iSLhsmGOCTLU7lVb629X3/9v//+SSjK//NExHYQOZ6cANTElI1AZVWFcq1/////3Y3OTXtNgMqvUfcpqNQca+BTO7xQBrwdx0liYC24vyKombhtxFjZ5xN6530Efv////+r/K9JH3QBQdP////orLNU9bYobfQN//NExIgQgZaUANzElIpTc2+BjNI02L6ugAADJ91LeJYBLSotIwCOhvzFYcgmAGkHhTJEoXOku+vXtp/+v/k8KLPmK/k0ihbmxBv////+6tIJ0LYmyvYcnzAIWGXfjTxG//NExJkRgZ6MANzElBCQNQVXLFxNxbTPJhhwJ0qyLDKhaWAcBoIIjWFgNU2MCc9f39f//J1FUV1FeT0buHFPnFvti////8nXFPX1VdYW4wITZw4inL6U86CZReqHr5Vs//NExKYRsZaQANyElN/AJ6qceEXwFKLC6yry3AaFcgFAHiMZOkwKChlZCJp8t6PTS4ucOosXODmgfC2W+0+BRQIgZWSSOUPWYu+bojCYtJGbGQGtWtV4fKvuQXHdDQ6F//NExLISiaaYANxElKrutfqijl1JJHULbFoJhMHG1TnSc3haLJmAZgKyg+XWbvl8Z8d+z/+nZJTyWhUHHRi78EgMFzARBJr0NFgHQEg83xyA1GdleE8XCqg0bmbdcUu9//NExLoSYTagANPQcMe27vnKr+Y75v8ycYAkvZHNbKqqmEpLRJLKSNZ7EVC60K9yjyqiNNA9nCCEZax6VMmQwMxFZQkMyqLzICDA46ijSj3DCAR0U0FGpD/ka7wO4Gms//NExMMSkZagANIMlKepiWI6NbrtKONXo9P/b++n7WC1M0DceDyoA4VnC60YrBcaUzMMA9hszBogAosCaOajzJrRoSioZ486jpR/eVpaZa9b7t/0HfZ63ehNKq2empe9//NExMsSqUJ4AOPMccxXUlWHYdfilJtBCbGofl6LTQv+5ONyaTyIF9xKIgAF9/UiXyfC5oOaJ4JP5w0KhfidhZIhUZQQT/Qzx8uCbgupAOOBEIfsGz/x2E2V1Im8GzgI//NExNMQKHpgAOPGSKgElgY0BXAA4xnf+pBnoLNz4akBIAkgs8OXDtifRUxTv/2dNSBo9DkILIHMHQQEZki4ssvjmFwrf//9vd/JxZDBKBZLRdImUC6ZEGHAii4aMiVA//NExOUQkE5YAVwAAKYJyFrPvQQr6C9kkL779be/55VSl+Mk6pxPCdJUpKnoFJt9Qui1UjmQk4s0QtGUBCQlhMoFYBpgFCM2hcJl5kKNCwjUitBJdmmkF1U7WnckKPfs//NExPUnKyp8AZiYANRuNRS/YhC4RWy2VoaoR7ibErNIUSTLrOMrKzaZgnjSEiIUTE4H1WFRhfZwi3JEvV+fASgQI7Ir5JOS/N4maYf+7GI7/NrrT69JmfWOTP1XEhyc//NExKshwwasAc1IAd8JBEistQiKnIq1eeGwil1eteOUJaO5mVWCUIwaGhMQPJS+IjY+Wupw7bcefD1U2y6FT5ovf56v4/ROonbazbDnctrROw2O/+UW/81fDH0zOo7b//NExHchQu6oAMsWuWudw6UjrZo2PYSl2yKn5Pf2y5RgmBSndSyvmZkgjKJAS//YSxUffywjWib/7cob3+9HcMxWWxlXELAsNavgKZDhy7zSM+jGE4XzhmfD6RkKeiHD//NExEUeQdqcANPemOgj9vNaquXcen3V7bf3mr2f5tl7M5xrVrpeltSvvWIMlXoMdrP6EVOkTRdzgLFJi08SNBR2n4w++hMBFYa3uXdm8GlphkQG3xtjL2au7+HHG79f//NExB8ZWcqgANPalDeOc2779ME2e5jPdpoABklKLIHRkm1BSiYWpPooGLXdxpBssu6o8mtWdNmbmLP6+yjhOIR5yxwY88Iis8bz79tFv539FXI1PBqOM/dAIExgEJs9//NExAwQgMqYAMMMcAymZKoIj7aeQ1okqe9latXf29Lo/sSJEnR9OC4Arc4JPWqsFcqCs6o9r/1Vu8Ff+Ivyz5H/6yQACWJ1MJzFIGQiE4bdwZ8QYEEyxtsTtLCMITJb//NExB0SiM5IANPMcDljwFcw0vWusW38bk7XOXnbTckGJhiTnhQ9q6tdSf+zO/aS///uklLw7s9yzCo5ukN2DrCMOGRAu6VFKzXnkDUnBwswgYFzgq+hzzDXRVKYDZYJ//NExCUQEDIsAM4YABhVZlUK9PQiiylG7bVQMer469jHnldzXDX2CaoHjJeh7hGNwLIjcUJjD5JWsqVw4v60OSyw+0WQsm6pLxZnUl58VIJrsKkBzDRVSYvmGHAcSLEl//NExDcQkCosANsMANSTi1WOHCi1rH6qagHdCgxLaAHGoZTfySeDhMYcTONawcsyXASQ2WelwfvIkDqVPTvn1tcsTi+57xccgVvIskDAxT6kr7b3hUbfclbggu11bhil//NExEcRyCYoAVoYANUUVxOLAeuFkezA2PhaR5PC4PsDa4AIEBQP7cBgAGIA6QRx+7qYLnBAALoACAAvZ/dmwNCZAsLL4GUFAFBBPn/+cHyI/BvAJ0HAGK///wxWKXEe//NExFIgyypsAZKgABdImMwVHD4P///w1YKUJMhhBBkyGDgEfmxOC5/////8Zsny0TZPmZQNBwGiYoAUAMgqdqP2GZxkZnuu0OViUlA6anlukg7ELNtVg1mipwfn3Uon//NExCEZSWK0AZhYAI3XZZ9Qkkkbf3STFTilCkDpZFOce3ShmDFquEmoK1y3mOmqxi1V6zYUU1UauTFT8WNFjSSt4MBmYnMeKTlCqMO+eQsN1UmmJOgFgyR/YEaovGxY//NExA4RsULEAdBIAAwINFTx1jaS5Ue8tm/P6QPj7mK2tooARNnMRiZDGNtsIo3aN0pajKwqksaiMAhooN2eLNKOdp+TpesvAB2XrIkTElNuViR5NUv5ouxbDXIgvajx//NExBoVEWa8AJYWlPqP53/1AE/rnzcSt54WQyDVK2miHUvIM7W83Hdcwga2/g4XO9MxOs2uWpRWXAuZSMaYs4oFmtCVD/oV/W7ispKyh1vZAOZ1vQgoWb+O9P0Fln4g//NExBgYobK0AMPelA/yvxvp5A4+KF7jz6sO1vj42iwah4VrEJtum8pCN/2FyvvUi3veNKZ5JWjWqJ59WZY+N1h0r7wbYv8xNYvp9YmKCzeeSBjY6D1ehbVnQNvJdqhq//NExAgTgVK4AJPelIqb52gqImOwiQmJ8XP0fzresrrP+VKhFsbynWbWctQ03Pe4J/N898PlqabvXsLXgxYGN+25rfPkiKCkqh6w1g40JH/+y+jmX8eE4VmnTOuwzA76//NExA0RGUKwAMvScFpDIKs2jbJiSWbfgHSqf/hFv8REi21g+FXwaVSlt1Qqa/pNC714xz2lHPeImpBzs9TxE9QCKnVKpJblK0nDnGWDpfcrCgAhdby+PJ7GYBThYmi2//NExBsSQeaUANtEmCeO8160ugSrO5gO01o1f+7dTeT5H///27uXZTGegKUyqGPH1P///e2hqAgWDYx+7UackwcTAfEJA0CVRnQMwtp1FxT2GPFEWzj4HUjvQQSso4ve//NExCUQiLKUANxaTF5Krb68VqF//0YFNAMNTgHB4lR//9XXYwOBgycNVRoEvUz0mI2pqZcwW5DgNFEwa/eTD95621BIXG87eW4vU24ccJGiqeV2frdIf//KuvtuKt////NExDUPyH6QAN5eSP4q4qVSEyJQkkkqElQkwyUCho4wnzGIlDiilkDAcUIBXWVVYWnMxKV1SGotWKJEqxFmTqNmSNBkgkRSwwCsDaHen//u963PpRV6V//u5toKiIiW//NExEgScIJ0AOYeSNGiB0hBwIBohJjcflogBDg8GVsBQVBwdlcDrBmFQFJ+VHlkEW7nTWTQnHiUcJlubUQO/9139XvoZ7O5+//6//Y5X9UBQqctDKZsAsbvh2ZdBKaN//NExFEQOGJkAVwYABSGAwaDwlmB4KCwVAwLUnjBICm5FtYwuOhDYfHCcLJUYkpOWHrKXqcXLIhmSKZVTDzCBUOSzUZTGOpNVVNV3VTTrI16spxprUd9WSe8xfRO1lJb//NExGMgewpUAZ1QASJdpzsehzL59TEPtPMXbaa9pMf0R6LS1W2upWA7JApszpteEJbopGnljF5UHrC4aSxB99IOmtjFCtRi5w3Nz7GljIJB2Xy80NDiJosoifhcoMjc//NExDQd0sqsAZhYAd7PoHCSVAng6JTiQgT60zd9sr3nJmmuLCSfqe/f/N/fDGtt3MTPz////y6vv7+Jfvmv///v///v6ckGheCvu+Mn4ZHqvZ63DLyi+3vwlMZZ4NrY//NExA8U0Uq4AdhIACfzcRZG49vmMpdCHJyrVQTrPUEbdUsdUQNwWEZwUZFkUn0Dj0DTD2GEj7Dba6syCa680TL7D5o/NKuQyNUXDBsnS9uGar2H/q+aKWO7wzFFlYLG//NExA4V6ga0AMPKmWHBbwHTHxNCE+Go/j/EJam/xtuLnPrc3MJGQe9ZWFUU8GKUBR9DYIqSlCmHOWYDnGoiDBRrsRydC/VVVUNFEa1b2MIHVijxcC2FT8zA6zStRmFl//NExAkSaVq8AIvMlOHN0tZPiJU/zQPxztb2bE7F/3iVXR6/T9TrOOxMmE5+9xuM2xTd/Z2PiZ54SXrs53zRJARO5tKALWpcOiJJoZCCdS3rtCFam9Wf4N3Lbg9MR5eq//NExBIWOVasAMPSlbCwoKL9MZfjlgUfWbEdjfxDRSqjZqwHeP19enFYcVyrkKY/+aiHP5MopRosVLIu0XoREz/VFN+C74ZL8YDwkS/3eV4GobO7JiNzOZHAx4CwODqh//NExAwRUUKQANPGcJ6GlZTCBRES5XhH07L8ltbynVSxR7xYTNurGQUY7SDGGVQQoGgEd17Gal/VVYyxgpBhRnf/+o9U+tUDSFXygiEgxhEj8pzFlOYLBb/QG0waBMen//NExBkR4JpgAVwQAKDQuFmXSq5lT14zZzuzAlqZcGZ72qsQxjBtagaUj1f7/T/56n93+kfU6619qCqlFgApIUCA4oVBL8pNRFUENMBRt1O64q9lndUSQcIVf2W7iqK4//NExCQZsyqYAZloABRAxfZ6SAXkL+QgVwIv+hfgEUABsUx5CWGv/+TSmShUam7f//mDMo0OM6f///83PJ0000ND/////QQUaePc2JQlzN3WGOPGkGcrQpjlJk/EonO///NExBARwUK0AdgwAL5lhruqenrtTbTVVP4+/5L3LFakUSgo44E/QEhBDEyGk0z75gzWINKMs/pZUH/sut//v6H/r+s1R2IsEaFznBygFJml/AZBoc+SkEAn38ooLc00//NExBwSGUq8AJrSlOk+/0SAHQx6OCcEB/ViJ7JO2+UipRApLlmBWjNNIpsI3Sqt30uMES/Th9ZNKm9gwkCKFzBIpgO0gr84I0CwPPk4dBzvrRJE3apSReHoy2QNgCgb//NExCYR+U68AJNSlDbUYpGySH3pNr7uSm6eytCUbUyFdU4au1N94Sav2MGqUlGrUdDuAS0wQPn4roCoKi+c5eh8x8ffhF+V+f/l7Bv9fGG2PXUCw9B4RBszKitx6w03//NExDEREVq4AJPQlDx2070tY1Ztjlav1Xi4z0NGjkIV1/81i/wbHP51u7xJkheb+/oQVHTYrmsh/b//ziNHnv8Q3z+8O7Nw6ylLc+Yif4hHiGw51+5fOtzm1Gj9QhQF//NExD8SgVqsAMvWlFiWYuCTb9adPr/qiZ/7YO0vj+73WEyJiqfk0TAojVuW+tLSY0RizI7KXtb///n3////5Cft+en7Ppr3fO6JfQhG0I0hBDznORT7nOHFooux3PUD//NExEgSUxq4AHlEvXzVAvM5Uv//S3//5f//////////81Ok1LoSpQ5Hm+5zHPV5FmNc5ZGcrpLuPDZ7MMj5EdY4bj46KSx5YuJI2B8VHCp5EFo4JY+qBRV/////r/+X//NExFER+x64ABBOvf3//wv+ntu2laPvVvpqll7e6lZlo5rIhWuVEMqxUzFh52YjsYrHFVFRIOiQkYYPExoAgYwsIqwTgKWJB4oROHS5VR1f/IRv/+Uv/wDGxv2bZsZW//NExFwSixqgAChKvf//Jbc5/+rbv+//09iV0rZ1teeRkU4mg1BBVyMIRcxGWKCJhGhBMXIofUZYYpB5AHEhAOFD54M8fUM9AGwE4lFY4WgjDEPMt28upDQUDJp/CQxR//NExGQRwx6sABBKvLPf0yTv9yekEGMkgeAydxSuz/Sd/////8NexXI4dLA0eLMWCsRKpv+VcASaVYtQmMM8Ulli5gCPg/la901KwDUO1RWpRSKGustR+I1DnK12clZd//NExHAQmMa4AHvMcFkYhIQBDlajHIm9PsmnKscIQTJOeKfW8CLJs9lF8zTBWnqWJvGCj3AEIKxzr1IHAKaSWmGpDD/QnX3ZRQaeG5JQ5lqGp0PBwTtpVHNH2q93E11///NExIASaUq8AHvKlKc9QgyRIHTYeNvLGXjDDggALf0q5z8pCFKlTS+xQP8kJ4wocUfQSJojQaAeEY+u1glCUqnLmJ7PHRVEk9q2sMT0FTwNByDR4iR0eJSJ46HbuVOl//NExIkSWVK8AJPQlIceeklbpq169IzAkQ4BBKAWnxXgHgk+u6lufPqSBTYTWjB8GpblnGtyBOGTOkYuS4CgmCondqmF+hR//WpA2JQ2WFUBUXKigCt///2+Kct9jwAn//NExJIRML6wAMvYTBCh7o5TlQGHgG1+no78wFB2tiGhga+XF8Tna+7O2NLf2bnyje3qXRffpbq3//vN1pdhRx4UNAM6Uel////2WjGlqP+iAYnwG4Aiu38h4w8bVD29//NExKAR+LKYAN4STJOGpVYWTLMA7gnhLOOICCDazDuD9SW0oPmDqrdurzJn+/t0/7c6bWLcj7exjOQwZAqQAbgr/9v3VCMAvGWIbWqRXpcpSdGSC8qonZdcSWtGhMvh//NExKsRMbqYANsElLbhIZ+cnXNwzqCNKsNJFpGsqQyiJ24H7yxqd5+9f//X8H7eN79ur+3+vU7MpxQ5r+qZEwEEiin/cjf4s+VQbOscuu0dIOAoxVix6sZfIMAgSJIX//NExLkUmdaMANtEmKYMMAkPBwUFgVZHPOGVkT/v4IDAVitpsM6cUwULL2F7yEk6VwsI0GOAUkSHl+T6NM7821id18rn8O67h+Wjq+jf6SY/9z8lACMywgBB00Yrfmlz//NExLkVIZaQANYElHDFAQdupAxurgHE/20dZ4Z/4f/feVDzbn/qdp+qxs9boc3Tn/cHCGK5albKJ+pLVgAVa/bpC67HZLFxUaGOU5aRoak5s6noIQL2feSlw21l8YmY//NExLcgMg6YAN5SmO9t4RntfCpS/ntNXOq3Ll/Octgw2rBERoRSaDQYBrSEoRSpVE7OjNa9Sz0lDDt24b7qpbcPi+ypmp9AtbAOltl1vrrTEQCHJxNhO3I8qqzCLj6t//NExIkeIh6kAM4SmOW53Fhqgl1F2h5yskjBBi6YHpMle3ywt53WVmzXXqv/V5FIRXHkBjndVYhb1oeiOMZWn97hpsCqGXf+ikVIkOCpisyh5etBeyOH53PGpr2rNzek//NExGMS4aa4AIPElBJCKjKmkJOCmTFBS3A3EaZZSf+X8zpTiNqbhMMIN1AOdjx2QcKYmm+u+8oOd2//0azARMH0SaCRAz2UU1ctr5lm/HSRRJqTp4/+UFiF5gbicUHI//NExGoRuaK4AJpGlISsIK6IPMNK1FrfRpXVUbdjRh2FhFZSme40cQMNJLb0rkDwhS+SSqzIP6AXC6kgJsfb5/lvK++G8yrWqtxK7UjjrwPQtQBxSzieLuXIGII25dhT//NExHYSaY68AJJKlMhJh03ChYO0gOGXEUpl6iJdyPqSqVwDR0VmWKEBHEkEyUFNd45iHYtiizIQOD5EW0TQYDXv0h616Rv4jNG25nKjRoDAAIgnd3l9p3d87uzU+peW//NExH8RKOa8AIvScHLosoEhpUdqWMgBg+v/SvsbGEFy9/H1NrNx/AvHmAa2SwfM7S4pZh0U/pfYBOfGBMGMWShYZMrakiRM8RKBoiN/6tl3//0b/d2dkWMy9W27AAXB//NExI0SKUq8AJvMlFzuBGzaz6NnFvmTOJkGDL18pZmZEGRLX/9////X/df/P/8TfdffHMLE78TxNPy9ql412m2MRt7HDDR8OHZTjESnhSHQUDsWCAsRokwiFDggSB6P//NExJcPmNa4AMJGcLNFgfBwsPghgQhFGVOqBDUN//////+ifN////f8f////99////x1y2u+XctbLWt+auWta5yprKLW9P57i56Y+kpOuylo7UIlM5ZZBOx1GrXDuNg//NExKsZSxa0AHhQuU4EJMDI7huNmnZQn///////Kv8v//9//7///2/2Xzp0dGndGO53oKOQiMRhMPkY5BlyEOMioTchw+YOFFgiHyiDCAiHHCxIUKBwcLD4+ioZIf////NExJgTsyKsABBWvP////YJnPX//3/9OT9fs9P+qLf1pWfcuiq+ruOMhEdBWQXIjnsZanD5xMOAUaKHi4sCjQGMUc5yFFwU4DGCas+Eeo3i8vl2QcpHOaPv/4//X/t6//NExJwQ4xqwABBKvXlToOhwRSMy/5///t/+y//29fvsXpelOVrbl3RDFK16lLQpBRSGCnASJXIrpXCq7us1gPpgWeVUFxYTbuAJ55vOepLQ3T+YWfmuYvdHl7QoY4YD//NExKsQ0xbAAAhKuaFDRVnHqcPZRxhrh4IREitf7bA4QPJp//+70U9H99VVw5eGQC1bVUhJbmJpgAJPXo+Y556tq3/6/29nFiCAguhwzrWZuxukpQ1C6yH2X3Jdf/nD//NExLoQot68AHiEuXIRjEK6j4RT0tQBy4XP2ggLGCFKljrgCqUr5tOmSA50t//yl1qi6Uff/owuODREhjh5zOzJb/yqzaNmXX/+3X8/tVsLtOsh8nUdn//V+cG/ur6w//NExMoQ6UKsAMnQcMavJOaia1YihfTbIGaIxgUHyyq4oye4QOJ2kBc3WgcCCMhRYuGxARyAIKDLC0jzBOSHAwjmkJFMjAkLf//////l/Pxf/////2n/4/X/9q+/j52///NExNkRqT6wAMHGcOvqtjonpNc4k2itVZpGCyjslImqJSxUzFBcgk8dyXRJouIokHiUOSjh8jAsHWIgqOOJVWBo////////5f/////////yf0I8lVRlF0xr2i6HQhUO//NExOUdwyKwAHlSvEFCCaoNAc8kWS93FRrCIfFzh8Bg5IJEFED5jCxWFBFxMaQRMmX//////9//z6bopGU7nIOUsaLDBRxcQCliRhQYCh4SILqJKHFNFhpAEDwkY4fD//NExMETSxq0AChQveLDBCjkAWClGBESQOhg92CSAMJi5hpxUhpSRlBCAbpu////jmQ1vcr//////v9r6WXMfty3+aaYqGKJKWpkM5gxgwoqSlE3qhjGdKuAlCiW3SY2//NExMYQ6x6wABBKvK0gp5QpZXoBAQEVJcvgMRIGHCxB/m7rrWOqRl7E23k1EDClsqLtMMkYIBQMUgDDmjYLIhU/JTc1ccNUK1Hu667ezJLCW6shtPdSsWwEFRj1lpHX//NExNUSMwq4AAgKuXfntVx72PofLFQEOaSVErAaKrWtPvsYtBGmhFGm2Za3mXAbLooYYBBKUoYGlfDtZy0JcmlIVHL/PM3IRgshY7TudFtgQNpg5WtySt3ab+v6FYqE//NExN8ROw64ABBEuQRR2+xayzUU1L3f/7v/UrEva4ZXcnxDwWHHqJpqvSCUpxXgsHWmAUJWXgGLJeKSqr6NwV4KLjUw2jNjIoWZPQA/lmksdAYfE7zBko0iZPi9XKBE//NExO0WYZaUAMpElCwfAgZOOVtkwYmxXitqAx///10Vw+CgJ6+U0WHBpGegAaovxERnmWshc7Bk1cxd9CGlUMEVQFFB0CCB4wcULlAX1iWIYiNnPlrDG/3PPmdf5vx///NExOYTqTqIAN5EcP//d712yvBsDQGgDhaJ9pY0b3nXTligM6gB4GE3T6zXsOHP/NaEJ8JI5g3MDeg+ZQDwdfWRZyrvbLV8pwYsJcBosI5w1R5NoVZckLJWqYalHGLC//NExOoV2JaQANawTHIZaMeOnKArIutX1GM0Pv+RjNHr7mO1WYBUlkGrIePj3uQ3/iarNKQLhH7VzgoQOGoAjGZEtTKndZN8pYp+EJoiCG7ThODyhnva7edS9AnIogUI//NExOUaAbKcAM4MlGHeTi03J67DlsY9lRdx8Ty77+62XcJ+LljHOn0+ttkpOsoguqFCCNVEYasZxdoexNj8uSE9h8ZuHRAJx2UjI7KNLlxKwXHUBCkoijNq51Odwhf9//NExNAVUZ6wAMPMlef782slXVuaqToJIHGZg0m4oHtP///9FaxjwcxcwwUhrNJlo/xYQX04ElTZKfTgSUxgZSn5NQzN1YYE7CQWl4nGZMWoQAMEEKRsbsbtyqir20Cl//NExM0R6T64AHvWcQ0Vg0Upf7K+ZxuhaZia7dGVr96MFnbkR7qe7hFupHzAjY8OsOG8hHWOFUJNZVihyx40ukSp02qWRSxorMCkD5qdNrX98x+/zGr7kWXmY3crJx1H//NExNgSWTa4AIMScNO2mpdQ0YMS//sRd/011HAHJe1KAOo7U+7VPp9fCxcejyNRurkwqMTklI8L8A8nZw6QzktNkAZjuYLyeCsVFg8GCQXUyrOa4VhZEUm9zRUcslNI//NExOESKZawAIMGldO+TS6Z5NG+whRJTea3/6Lf/xyjyKXGoWCQNMo441sfy/fO6yvS2pyX43crVo8ahPGnl5fXqBRBpNYIQlepUIIuq+sOHJ6P7Ze7u7Oft+n56t9t//NExOsUmYaoAMPMlFgmbT98uzU7lpM1O7YjCVLNO0Q0HVlhur/wwpbLZV/h/AMOMBsbSNjvASKACJgYAUBj1BkRpcMOmJ1AzqECzIBcEBoBogsF6Q/UQaGzGq3U4GWC//NExOsWsaagAHsQlITDhayKkAoBFxiziTIKYmRZ/GfD8gtyLQDcQXND8YmpNKdv8G7i4JEOMniuVaSJkkkYrb/5MnCHEkWCgVyKrPGZe+r//8mj5SHETUN1KjxkJwYs//NExOMR4WqkAVhgAbS2L+/P3LPFI7JmQd3vYhVQqseG6D46SBbXAsXB8LQDaFNoqy6IECjzATQg9HARsCAYSPFssLIp//rpBWwkicKmfwf///+cWcHALjUnnKra399d//NExO4lSopgAZqgAGlVml5jg4q/CkHii7gOgUNpBqeHp7ulklHaTpBv7dNbtH2fT/Vr9dUM4I0dSufK6N8VrUIQhsThIR/MIVVWbpproQQWoLCwNPlRoKgsDQNP0ESr//NExKsQAN4gAcxIAIktxIrqPZY9nv/ungVPZY9v3LgtpUxBTUUzLjEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExL4PyNIUAHmYcDEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExNEP8Mn0AHhQcDEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVTEFNRTMu//NExKwAAANIAAAAADEwMFVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVV//NExKwAAANIAAAAAFVVVVVVVVVVVVVVVV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type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : apa saja program di Kampus Merdeka?\n",
            "1/1 [==============================] - 0s 34ms/step\n",
            "🤖 KadekBot :  Mau tau tentang apa nih?\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : Siapa penciptamu?\n",
            "1/1 [==============================] - 0s 42ms/step\n",
            "🤖 KadekBot :  Pembuat KadekBot dari kalangan mahasiswa dan mahasiswi lho!\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : keren!\n",
            "1/1 [==============================] - 0s 25ms/step\n",
            "🤖 KadekBot :  Helo! Ini Kadekbot. Lagi kepo tentang kampus merdeka ya?\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : terima kasih\n",
            "1/1 [==============================] - 0s 47ms/step\n",
            "🤖 KadekBot :  Sama-sama yaa\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : goodbye\n",
            "1/1 [==============================] - 0s 29ms/step\n",
            "🤖 KadekBot :  Halo! Saya Kadekbot, salam kenal ya! Mau tau tentang kampus merdeka, kan?\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n",
            "👨‍🦰 Kamu : bye\n",
            "1/1 [==============================] - 0s 27ms/step\n",
            "🤖 KadekBot :  Bye!\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" >\n",
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "============================================================\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Save The Model (Simpan Model)**\n",
        "\n",
        "Setelah pengujian Chatbot telah disesuaikan dengan kalimat dan jawabannya. Maka, model chatbot bisa disimpan dengan format .h5 atau .pkl (pickle) untuk penggunaan aplikasi AI Chatbot dengan website atau sistem Android. Penyimpanan file model bisa langsung secara transient file lokal komputer atau bisa taruh dalam cloud storage di Google Drive."
      ],
      "metadata": {
        "id": "PpFwQ9gWmWtk"
      },
      "id": "PpFwQ9gWmWtk"
    },
    {
      "cell_type": "code",
      "source": [
        "# Simpan model dalam bentuk format file .h5 atau .pkl (pickle)\n",
        "model.save('chat_model.h5')\n",
        "\n",
        "print('Model Created Successfully!')"
      ],
      "metadata": {
        "id": "MxdDHujDmaC0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1ea42bc5-3f58-4143-f4f3-bd1938d89926"
      },
      "id": "MxdDHujDmaC0",
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Created Successfully!\n"
          ]
        }
      ]
    }
  ],
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      "display_name": "Python 3 (ipykernel)",
      "language": "python",
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    "latex_envs": {
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      "autocomplete": true,
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      "cite_by": "apalike",
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      "eqLabelWithNumbers": true,
      "eqNumInitial": 1,
      "hotkeys": {
        "equation": "Ctrl-E",
        "itemize": "Ctrl-I"
      },
      "labels_anchors": false,
      "latex_user_defs": false,
      "report_style_numbering": false,
      "user_envs_cfg": false
    },
    "varInspector": {
      "cols": {
        "lenName": 16,
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        "lenVar": 40
      },
      "kernels_config": {
        "python": {
          "delete_cmd_postfix": "",
          "delete_cmd_prefix": "del ",
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    "colab": {
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