feat: download dataset from Google Drive when running locally

- Add  dep to requirements.txt
- Non-Colab path: download dataset_jagung.zip from Drive using file ID
  if not present locally, then extract as usual
- Keeps Colab path unchanged (drive.mount)

Co-Authored-By: Claude <noreply@anthropic.com>

Machine_Learning/notebook.ipynb

@@ -170,7 +170,7 @@
     "outputId": "30228ce8-1b64-47f5-93f7-30632b2af1c5"
    },
    "outputs": [],
-   "source": "if IS_COLAB:\n    drive.mount('/content/drive')\n    archive_path = '/content/drive/MyDrive/jagung/dataset_jagung.zip'\n    destination_path = '/content/dataset_jagung.zip'\n    extract_path = '/content/dataset'\nelse:\n    # Local: dataset assumed at Machine_Learning/dataset_jagung.zip\n    base = os.getcwd()\n    archive_path = os.path.join(base, 'dataset_jagung.zip')\n    destination_path = archive_path  # no copy needed\n    extract_path = os.path.join(base, 'dataset')\n\nif oLine truncated
+   "source": "if IS_COLAB:\n    drive.mount('/content/drive')\n    archive_path = '/content/drive/MyDrive/jagung/dataset_jagung.zip'\n    destination_path = '/content/dataset_jagung.zip'\n    extract_path = '/content/dataset'\nelse:\n    import gdown\n    base = os.getcwd()\n    archive_path = os.path.join(base, 'dataset_jagung.zip')\n    destination_path = archive_path\n    extract_path = os.path.join(base, 'dataset')\n    # If dataset doesn't exist locally, download from Google Drive\n    DRILine truncated
   },
   {
    "cell_type": "markdown",

Machine_Learning/requirements.txt

@@ -1,5 +1,6 @@
 tensorflow==2.19.0              # CPU + Colab; for local GPU, install tensorflow[and-cuda]
 tensorflowjs==4.22.0
+gdown                           # download dataset from Google Drive
 numpy
 matplotlib
 seaborn