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MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25h" + ] + } + ], + "source": [ + "\n", + "!pip -q install stanza pandas\n" + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "import stanza\n", + "\n", + "# Mengunduh model Bahasa Indonesia\n", + "stanza.download(\"id\")\n", + "\n", + "# Membuat pipeline POS Tagging\n", + "nlp = stanza.Pipeline(\n", + " lang=\"id\",\n", + " processors=\"tokenize,pos\",\n", + " verbose=False\n", + ")\n", + "\n", + "print(\"Model POS Tagging Bahasa Indonesia berhasil disiapkan!\")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 254, + "referenced_widgets": [ + "17b9474f79034385a89897499533063b", + "d9ab537b954d4fcdae8a7cb95ab5f26b", + "5907888b3a8e46648f3ab2c0e7780d70", + "3faed7bcfa104073bd843ad5081cef39", + "20c14d2e8aa649789f914b3dbbc2032b", + "a311c909c8284916bd17b1d79812d022", + "74129ea9231247719ad8bf23ec6faaf7", + "8e2adb7cc4474ead808af9c3ef565463", + "3d4946f06c1448d18a1e6cc22c3ead46", 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}, + "execution_count": 2, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Downloading https://raw.githubusercontent.com/stanfordnlp/stanza-resources/main/resources_1.15.0.json: 0%| …" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "17b9474f79034385a89897499533063b" + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "INFO:stanza:Downloaded file to /root/.cache/stanza/1.15.0/resources/resources.json\n", + "INFO:stanza:Downloading default packages for language: id (Indonesian) ...\n", + "Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n", + "WARNING:huggingface_hub.utils._http:Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "models/default.zip: reconstructing file: 0%| | 0.00B / 394MB " + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "a6d358077a174721969e2b2d6e91e58f" + } + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "models/default.zip: downloading bytes: | 0.00B " + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "8986c74367554ac49cdb0471bc4186e2" + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "INFO:stanza:Downloaded file to /root/.cache/stanza/1.15.0/resources/id/default.zip\n", + "INFO:stanza:Finished downloading models and saved to /root/.cache/stanza/1.15.0/resources\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Model POS Tagging Bahasa Indonesia berhasil disiapkan!\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "import pandas as pd\n", + "\n", + "def pos_tagging(kalimat):\n", + " \"\"\"\n", + " Memberikan label kelas kata pada kalimat Bahasa Indonesia.\n", + " \"\"\"\n", + " doc = nlp(kalimat)\n", + " hasil = []\n", + "\n", + " for sentence in doc.sentences:\n", + " for word in sentence.words:\n", + " hasil.append({\n", + " \"Kata\": word.text,\n", + " \"POS Tag\": word.upos,\n", + " \"Penjelasan\": word.upos\n", + " })\n", + "\n", + " return pd.DataFrame(\n", + " hasil,\n", + " columns=[\"Kata\", \"POS Tag\", \"Penjelasan\"]\n", + " )\n", + "\n", + "print(\"Fungsi POS Tagging berhasil dibuat.\")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "AYgpSkjnOhzj", + "outputId": "5ef399f2-307f-4de0-801c-d76f456869f5" + }, + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Fungsi POS Tagging berhasil dibuat.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "kalimat = \"Mahasiswa Universitas Bhayangkara belajar Python di laboratorium.\"\n", + "\n", + "hasil = pos_tagging(kalimat)\n", + "\n", + "print(\"Kalimat:\", kalimat)\n", + "display(hasil)\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 317 + }, + "id": "Otgve225OkYs", + "outputId": "f88c62ff-dd4f-4577-a76b-e1168b605570" + }, + "execution_count": 4, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Kalimat: Mahasiswa Universitas Bhayangkara belajar Python di laboratorium.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + " Kata POS Tag Penjelasan\n", + "0 Mahasiswa PROPN PROPN\n", + "1 Universitas PROPN PROPN\n", + "2 Bhayangkara PROPN PROPN\n", + "3 belajar VERB VERB\n", + "4 Python PROPN PROPN\n", + "5 di ADP ADP\n", + "6 laboratorium NOUN NOUN\n", + "7 . 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Nomor KalimatKalimatKataPOS Tag
01Saya sedang belajar pemrograman Python.SayaPRON
11Saya sedang belajar pemrograman Python.sedangAUX
21Saya sedang belajar pemrograman Python.belajarVERB
31Saya sedang belajar pemrograman Python.pemrogramanNOUN
41Saya sedang belajar pemrograman Python.PythonPROPN
51Saya sedang belajar pemrograman Python..PUNCT
62Mahasiswa membaca buku di perpustakaan.MahasiswaPROPN
72Mahasiswa membaca buku di perpustakaan.membacaVERB
82Mahasiswa membaca buku di perpustakaan.bukuNOUN
92Mahasiswa membaca buku di perpustakaan.diADP
102Mahasiswa membaca buku di perpustakaan.perpustakaanNOUN
112Mahasiswa membaca buku di perpustakaan..PUNCT
123Dosen menjelaskan materi kecerdasan buatan.DosenPROPN
133Dosen menjelaskan materi kecerdasan buatan.menjelaskanVERB
143Dosen menjelaskan materi kecerdasan buatan.materiNOUN
153Dosen menjelaskan materi kecerdasan buatan.kecerdasanNOUN
163Dosen menjelaskan materi kecerdasan buatan.buatanNOUN
173Dosen menjelaskan materi kecerdasan buatan..PUNCT
184Indonesia memiliki banyak bahasa daerah.IndonesiaPROPN
194Indonesia memiliki banyak bahasa daerah.memilikiVERB
204Indonesia memiliki banyak bahasa daerah.banyakADV
214Indonesia memiliki banyak bahasa daerah.bahasaNOUN
224Indonesia memiliki banyak bahasa daerah.daerahNOUN
234Indonesia memiliki banyak bahasa daerah..PUNCT
245Teknologi berkembang dengan sangat cepat.TeknologiPROPN
255Teknologi berkembang dengan sangat cepat.berkembangVERB
265Teknologi berkembang dengan sangat cepat.denganADP
275Teknologi berkembang dengan sangat cepat.sangatADV
285Teknologi berkembang dengan sangat cepat.cepatADJ
295Teknologi berkembang dengan sangat cepat..PUNCT
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KataPOS TagPenjelasan
0SistemPROPNPROPN
1komputerNOUNNOUN
2memprosesVERBVERB
3dataNOUNNOUN
4denganSCONJSCONJ
5cepatADJADJ
6.PUNCTPUNCT
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Proyek ini\n", + "mengimplementasikan Part-of-Speech (POS) Tagging\n", + "pada teks Bahasa Indonesia menggunakan Python dan\n", + "library Stanza.\n", + "\n", + "POS Tagging merupakan proses pemberian label kelas\n", + "kata pada setiap kata dalam kalimat, seperti kata\n", + "benda, kata kerja, kata sifat, dan kata keterangan.\n", + "\n", + "## Tujuan\n", + "1. Memahami konsep POS Tagging dalam NLP.\n", + "2. Mengidentifikasi kelas kata dalam kalimat Bahasa Indonesia.\n", + "3. Mengimplementasikan POS Tagging menggunakan Python.\n", + "4. Menampilkan hasil pelabelan kelas kata dalam tabel.\n", + "5. Menyimpan hasil pemrosesan ke dalam file CSV.\n", + "\n", + "## Teknologi yang Digunakan\n", + "- Python\n", + "- Google Colab\n", + "- Stanza\n", + "- Pandas\n", + "- GitLab\n", + "\n", + "## Dataset\n", + "Proyek ini menggunakan model Bahasa Indonesia dari\n", + "Stanza untuk melakukan prediksi POS Tagging.\n", + "\n", + "Sebagai sumber korpus berlabel, proyek ini juga\n", + "menggunakan dataset Universal Dependencies Indonesian-GSD.\n", + "\n", + "Repository dataset:\n", + "https://github.com/UniversalDependencies/UD_Indonesian-GSD\n", + "\n", + "## Metode\n", + "1. Menyiapkan lingkungan Python.\n", + "2. Menginstal library Stanza dan Pandas.\n", + "3. Mengunduh model Bahasa Indonesia.\n", + "4. Memproses kalimat dan melakukan POS Tagging.\n", + "5. Menampilkan kata beserta label kelas katanya.\n", + "6. Menyimpan hasil pemrosesan ke CSV.\n", + "\n", + "Catatan: model Stanza yang digunakan pada implementasi\n", + "awal merupakan model yang telah dilatih sebelumnya.\n", + "Dataset Indonesian-GSD diunduh sebagai sumber korpus\n", + "dan belum berarti digunakan untuk melatih ulang model.\n", + "\n", + "## Struktur Repository\n", + "- POS_Tagging_Bahasa_Indonesia.ipynb\n", + "- README.md\n", + "- hasil_pos_tagging.csv\n", + "\n", + "## Cara Menjalankan\n", + "1. Buka file notebook di Google Colab.\n", + "2. Jalankan sel kode secara berurutan.\n", + "3. Tunggu proses instalasi dan pengunduhan model.\n", + "4. Masukkan kalimat Bahasa Indonesia.\n", + "5. Periksa hasil POS Tagging.\n", + "6. Unduh hasil dalam format CSV.\n", + "\n", + "## Batasan\n", + "Hasil prediksi dapat mengandung kesalahan, khususnya\n", + "pada kata ambigu, nama khusus, atau kalimat informal.\n", + "Hasil perlu diperiksa kembali untuk memastikan\n", + "ketepatan pelabelan kelas kata.\n", + "\n", + "## Sumber Referensi\n", + "- Stanza: https://stanfordnlp.github.io/stanza/\n", + "- Universal Dependencies:\n", + " https://universaldependencies.org/\n", + "- UD Indonesian-GSD:\n", + " https://github.com/UniversalDependencies/UD_Indonesian-GSD\n" + ], + "metadata": { + "id": "AvAKlJNFPZsz" + } + } + ] +} \ No newline at end of file