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      "abstract": "Pembangunan Ibu Kota Nusantara (IKN) sebagai proyek strategis nasional\r\nmenimbulkan beragam respons dari masyarakat, khususnya terkait dampaknya\r\nterhadap sektor pendidikan. Media sosial Twitter (X) menjadi sarana utama bagi\r\nwarganet untuk menyampaikan opini, baik yang bersifat mendukung, menolak,\r\nmaupun netral. Banyaknya data opini yang muncul secara cepat dan masif\r\nmenyebabkan analisis manual menjadi tidak efektif, sehingga diperlukan\r\npendekatan komputasi untuk mengidentifikasi dan mengukur kecenderungan\r\nsentimen publik secara objektif. Ketidakstabilan dan tingginya variasi sentimen\r\ntersebut berpotensi memengaruhi persepsi publik serta pengambilan kebijakan di\r\nsektor pendidikan. \r\nPenelitian ini bertujuan untuk menganalisis dan membandingkan kinerja\r\nalgoritma Naive Bayes dan Support Vector Machine (SVM) dalam\r\nmengklasifikasikan sentimen warganet Twitter terkait isu IKN pada sektor\r\npendidikan. Data penelitian berupa 2.006 tweet berbahasa Indonesia yang\r\ndikumpulkan melalui proses crawling. Tahapan penelitian meliputi prapemrosesan\r\n\r\nteks (cleaning, case folding, tokenisasi, stopword removal, dan\r\nstemming), pelabelan sentimen otomatis menggunakan IndoBERT,\r\npenyeimbangan data dengan oversampling, ekstraksi fitur menggunakan TF-IDF,\r\nserta evaluasi model menggunakan confusion matrix dan Stratified K-Fold Cross-Validation.",
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      "date": "2026-02-24",
      "department": "Fakultas Ilmu Komputer",
      "institution": "Universitas AMIKOM Yogyakarta",
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      "keywords": "Analisis Sentimen, Twitter, Ibu Kota Nusantara, Pendidikan, Naive\r\nBayes, Support Vector Machine, Sentiment Analysis, Twitter, Nusantara Capital City (IKN), Education.",
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