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belajar di kampus\"\n", + "tokenized_kalimat = kalimat.split()\n", + "\n", + "print(f\"Kalimat: '{kalimat}'\\n{'-'*40}\")\n", + "\n", + "# ==========================================\n", + "# 1. PENDEKATAN RULE-BASED (Berbasis Aturan/Kamus)\n", + "# ==========================================\n", + "# Pendekatan ini menggunakan kamus statis atau aturan regex.\n", + "# Sangat cepat namun tidak fleksibel terhadap kata baru.\n", + "def rule_based_pos_tagging(tokens):\n", + " # Kamus sederhana untuk bahasa Indonesia (Universal POS Tags)\n", + " kamus_pos = {\n", + " \"ariq\": \"PROPN\", # Proper Noun (Nama diri)\n", + " \"sedang\": \"ADV\", # Adverb (Kata keterangan waktu/aspek)\n", + " \"belajar\": \"VERB\", # Verb (Kata kerja)\n", + " \"di\": \"ADP\", # Adposition/Preposition (Kata depan)\n", + " \"kampus\": \"NOUN\" # Noun (Kata benda)\n", + " }\n", + "\n", + " hasil = [(kata, kamus_pos.get(kata.lower(), \"UNK\")) for kata in tokens]\n", + " return hasil\n", + "\n", + "print(\"1. Hasil Pendekatan Rule-Based:\")\n", + "print(rule_based_pos_tagging(tokenized_kalimat))\n", + "print(\"-\" * 40)\n", + "\n", + "\n", + "# ==========================================\n", + "# 2. PENDEKATAN STATISTIK (Unigram/HMM dengan NLTK)\n", + "# ==========================================\n", + "# Pendekatan ini menghitung probabilitas frekuensi kemunculan tag untuk setiap kata\n", + "# berdasarkan korpus pelatihan. Di sini kita menggunakan UnigramTagger dari NLTK.\n", + "def statistical_pos_tagging(tokens):\n", + " # Mock data pelatihan (Korpus sederhana)\n", + " data_latih = [\n", + " [('ariq', 'PROPN'), ('sedang', 'ADV'), ('belajar', 'VERB'), ('di', 'ADP'), ('kampus', 'NOUN')],\n", + " [('saya', 'PRON'), ('sedang', 'ADV'), ('makan', 'VERB'), ('di', 'ADP'), ('rumah', 'NOUN')],\n", + " [('budi', 'PROPN'), ('belajar', 'VERB'), ('python', 'NOUN')]\n", + " ]\n", + "\n", + " # Melatih model statistik berbasis frekuensi (Unigram)\n", + " unigram_tagger = UnigramTagger(data_latih)\n", + "\n", + " # Melakukan tagging\n", + " hasil = unigram_tagger.tag(tokens)\n", + " return hasil\n", + "\n", + "print(\"2. Hasil Pendekatan Statistik (NLTK Unigram):\")\n", + "print(statistical_pos_tagging(tokenized_kalimat))\n", + "print(\"-\" * 40)\n", + "\n", + "\n", + "# ==========================================\n", + "# 3. PENDEKATAN MACHINE LEARNING (Deep Learning dengan Stanza)\n", + "# ==========================================\n", + "def machine_learning_pos_tagging(teks):\n", + " print(\"Mengunduh/Memeriksa model bahasa Indonesia... (Hanya butuh waktu sesaat)\")\n", + " # Download model bahasa Indonesia (hanya didownload sekali)\n", + " stanza.download('id', processors='tokenize,pos')\n", + "\n", + " # Inisialisasi pipeline NLP bahasa Indonesia\n", + " nlp = stanza.Pipeline('id', processors='tokenize,pos', use_gpu=False)\n", + "\n", + " # Memproses teks\n", + " doc = nlp(teks)\n", + "\n", + " # Mengambil token dan POS tag-nya (Universal POS tags: upos)\n", + " hasil = []\n", + " for sentence in doc.sentences:\n", + " for word in sentence.words:\n", + " hasil.append((word.text, word.upos))\n", + "\n", + " return hasil\n", + "\n", + "print(\"3. Hasil Pendekatan Machine Learning (Stanza - Stanford NLP):\")\n", + "print(machine_learning_pos_tagging(kalimat))\n", + "print(\"-\" * 40)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000, + "referenced_widgets": [ + "cde6d6501e204d78a2424db0fb8575b5", + "0b3226f5b7f8435aac7898fce3fe42f9", + "d865ff95828f474f906310db8e573394", + "f9d3d432679e464d958d8f8fb04462d9", + "5fcc5c7a59d84f18be80d95ab1182333", + "15e5a67ad2544161a5fe7d4a1395d62e", + "060f55e57ba144b393de4a8294115ff9", + "14171aed4b464a0a8eb0e0539a7d7c54", + "cc459cc49a364019968f4bf87aa7ea6a", + "7a53dffa7dd84f0a97f32d4ab3852eed", + "108861bc6bea4d71913694af081684df", + "3dd635e6bd1243bf8397b13209c03194", + "2ad786c666b54ffea1b8b6c204f8f426", + "15bfd3491edb4e4a9266209837be8a40", + "95de3025222c4bbeab0206cceb9909db", + "26a217222a5e45fca11b659b3704a84b", + "94a7cd2948e24f39b848db4d0035d61f", + "c2611f7633ac452690b84db500e1dd85", + "400d04310ade4037b73e477b48f9b13c", + 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Hasil Pendekatan Rule-Based:\n", + "[('ariq', 'PROPN'), ('sedang', 'ADV'), ('belajar', 'VERB'), ('di', 'ADP'), ('kampus', 'NOUN')]\n", + "----------------------------------------\n", + "2. Hasil Pendekatan Statistik (NLTK Unigram):\n", + "[('ariq', 'PROPN'), ('sedang', 'ADV'), ('belajar', 'VERB'), ('di', 'ADP'), ('kampus', 'NOUN')]\n", + "----------------------------------------\n", + "3. Hasil Pendekatan Machine Learning (Stanza - Stanford NLP):\n", + "Mengunduh/Memeriksa model bahasa Indonesia... (Hanya butuh waktu sesaat)\n" + ] + }, + { + "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": "cde6d6501e204d78a2424db0fb8575b5" + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "INFO:stanza:Downloaded file to /root/.cache/stanza/1.15.0/resources/resources.json\n", + "WARNING:stanza:Language id package default expects mwt, which has been added\n", + "INFO:stanza:Downloading these customized packages for language: id (Indonesian)...\n", + "==================================\n", + "| Processor | Package |\n", + "----------------------------------\n", + "| tokenize | gsd_nocharlm |\n", + "| mwt | gsd |\n", + "| pos | gsd_charlm |\n", + "| forward_charlm | oscar2023 |\n", + "| backward_charlm | oscar2023 |\n", + "| pretrain | conll17 |\n", + "==================================\n", + "\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/tokenize/gsd_nocharlm.pt: reconstructing file: 0%| | 0.00B / 660kB " + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "3dd635e6bd1243bf8397b13209c03194" + } + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "models/tokenize/gsd_nocharlm.pt: downloading bytes: | 0.00B " + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "b8ba041afe5045aa86ddf2c96c4773f5" + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "INFO:stanza:Downloaded file to /root/.cache/stanza/1.15.0/resources/id/tokenize/gsd_nocharlm.pt\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "models/mwt/gsd.pt: reconstructing file: 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"INFO:stanza:Checking for updates to resources.json in case models have been updated. Note: this behavior can be turned off with download_method=None or download_method=DownloadMethod.REUSE_RESOURCES\n" + ] + }, + { + "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": "1969fa92d06a44c785dbfbaeb75275f7" + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "INFO:stanza:Downloaded file to /root/.cache/stanza/1.15.0/resources/resources.json\n", + "WARNING:stanza:Language id package default expects mwt, which has been added\n", + "INFO:stanza:Loading these models for language: id (Indonesian):\n", + "============================\n", + "| Processor | Package |\n", + "----------------------------\n", + "| tokenize | gsd_nocharlm |\n", + "| mwt | gsd |\n", + "| pos | gsd_charlm |\n", + "============================\n", + "\n", + "INFO:stanza:Using device: cpu\n", + "INFO:stanza:Loading: tokenize\n", + "INFO:stanza:Loading: mwt\n", + "INFO:stanza:Loading: pos\n", + "INFO:stanza:Done loading processors!\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "[('ariq', 'PROPN'), ('sedang', 'AUX'), ('belajar', 'VERB'), ('di', 'ADP'), ('kampus', 'NOUN')]\n", + "----------------------------------------\n" + ] + } + ] + } + ] +} \ No newline at end of file