{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "kjLcG0OCTF2h",
        "outputId": "bf21b7d7-1401-416a-c5d5-c7598696b4f1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=== Linear Regression Evaluation ===\n",
            "MAE  : 120666.43851956047\n",
            "MSE  : 30376148231.75463\n",
            "RMSE : 174287.54468336122\n",
            "R²   : 0.997055498513006\n",
            "\n",
            "=== Cross Validation (R² Scores) ===\n",
            "[0.9970555  0.99472634 0.99350626 0.99799496 0.99572175]\n",
            "Average R²: 0.9958009623491548\n",
            "\n",
            "=== Random Forest Evaluation ===\n",
            "MAE  : 51227.22032142918\n",
            "MSE  : 6343955339.2629385\n",
            "RMSE : 79648.95064759447\n",
            "R²   : 0.9993850508699337\n",
            "\n",
            "=== Visualisasi Linear Regression ===\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "=== Visualisasi Random Forest ===\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "=== Visualisasi Perbandingan R² ===\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# === Import library ===\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split, KFold, cross_val_score\n",
        "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.ensemble import RandomForestRegressor\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# === Load dataset ===\n",
        "df = pd.read_csv(\"Rice Production Indonesia 2020-2022.csv\")\n",
        "\n",
        "# === Encoding provinsi & siapkan fitur-target ===\n",
        "df_encoded = df.copy()\n",
        "df_encoded[\"Provinsi\"] = df_encoded[\"Provinsi\"].astype(\"category\").cat.codes\n",
        "X = df_encoded.drop(\"Production.(ton)\", axis=1)\n",
        "y = df_encoded[\"Production.(ton)\"]\n",
        "\n",
        "# === Train-test split ===\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# === Linear Regression (train & prediksi) ===\n",
        "linreg = LinearRegression()\n",
        "linreg.fit(X_train, y_train)\n",
        "y_pred = linreg.predict(X_test)\n",
        "\n",
        "# === Evaluasi Linear Regression ===\n",
        "mae = mean_absolute_error(y_test, y_pred)\n",
        "mse = mean_squared_error(y_test, y_pred)\n",
        "rmse = np.sqrt(mse)\n",
        "r2 = r2_score(y_test, y_pred)\n",
        "print(\"=== Linear Regression Evaluation ===\")\n",
        "print(\"MAE  :\", mae)\n",
        "print(\"MSE  :\", mse)\n",
        "print(\"RMSE :\", rmse)\n",
        "print(\"R²   :\", r2)\n",
        "\n",
        "# === Cross-validation (KFold) ===\n",
        "kf = KFold(n_splits=5, shuffle=True, random_state=42)\n",
        "cv_scores = cross_val_score(linreg, X, y, cv=kf, scoring='r2')\n",
        "print(\"\\n=== Cross Validation (R² Scores) ===\")\n",
        "print(cv_scores)\n",
        "print(\"Average R²:\", np.mean(cv_scores))\n",
        "\n",
        "# === Random Forest (train & prediksi) ===\n",
        "rf = RandomForestRegressor(n_estimators=200, random_state=42)\n",
        "rf.fit(X_train, y_train)\n",
        "y_pred_rf = rf.predict(X_test)\n",
        "\n",
        "# === Evaluasi Random Forest ===\n",
        "mae_rf = mean_absolute_error(y_test, y_pred_rf)\n",
        "mse_rf = mean_squared_error(y_test, y_pred_rf)\n",
        "rmse_rf = np.sqrt(mse_rf)\n",
        "r2_rf = r2_score(y_test, y_pred_rf)\n",
        "print(\"\\n=== Random Forest Evaluation ===\")\n",
        "print(\"MAE  :\", mae_rf)\n",
        "print(\"MSE  :\", mse_rf)\n",
        "print(\"RMSE :\", rmse_rf)\n",
        "print(\"R²   :\", r2_rf)\n",
        "\n",
        "# === Visualisasi: Linear Regression (Actual vs Predicted) ===\n",
        "print(\"\\n=== Visualisasi Linear Regression ===\")\n",
        "plt.figure(figsize=(8,6))\n",
        "plt.scatter(range(len(y_test)), y_test, label=\"Actual\", s=60, alpha=0.8)\n",
        "plt.scatter(range(len(y_test)), y_pred, label=\"Predicted\", s=60, marker='^', alpha=0.8)\n",
        "plt.title(\"Linear Regression\")\n",
        "plt.xlabel(\"Sample Index\")\n",
        "plt.ylabel(\"Production (ton)\")\n",
        "plt.legend()\n",
        "plt.grid(True, linestyle='--', alpha=0.5)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# === Visualisasi: Random Forest (Actual vs Predicted) ===\n",
        "print(\"\\n=== Visualisasi Random Forest ===\")\n",
        "plt.figure(figsize=(8,6))\n",
        "plt.scatter(range(len(y_test)), y_test, label=\"Actual\", s=60, alpha=0.8)\n",
        "plt.scatter(range(len(y_test)), y_pred_rf, label=\"Predicted\", s=60, marker='^', alpha=0.8, color='green')\n",
        "plt.title(\"Random Forest\")\n",
        "plt.xlabel(\"Sample Index\")\n",
        "plt.ylabel(\"Production (ton)\")\n",
        "plt.legend()\n",
        "plt.grid(True, linestyle='--', alpha=0.5)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# === Visualisasi: Perbandingan R² ===\n",
        "print(\"\\n=== Visualisasi Perbandingan R² ===\")\n",
        "plt.figure(figsize=(8,6))\n",
        "bars = plt.bar([\"Linear Regression\", \"Random Forest\"],\n",
        "               [r2, r2_rf],\n",
        "               width=0.5,\n",
        "               edgecolor='black')\n",
        "\n",
        "for bar in bars:\n",
        "    height = bar.get_height()\n",
        "    plt.text(bar.get_x() + bar.get_width()/2, height + 0.01, f\"{height:.3f}\",\n",
        "             ha='center', fontsize=12)\n",
        "\n",
        "plt.ylabel(\"R² Score\")\n",
        "plt.title(\"Model Performance Comparison\")\n",
        "plt.grid(axis='y', linestyle='--', alpha=0.4)\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    }
  ]
}