Penerapan Algoritma Naïve Bayes Pada Analisa Sentimen Twitter Terhadap Opini Publik Badan Pangan Nasional
DOI:
https://doi.org/10.22441/jitkom.v9i1.007Keywords:
Analisa Sentimen, Naïve Bayes, Badan Pangan Nasional, Klasifikasi, TwitterAbstract
Penelitian ini fokus pada penerapan algoritma Naïve Bayes untuk menganalisis sentimen Twitter terhadap Badan Pangan Nasional (BAPANAS). Dalam era digital, media sosial, khususnya Twitter, menjadi saluran utama masyarakat untuk menyampaikan opini terkait instansi pemerintah. Algoritma Naïve Bayes digunakan untuk mengklasifikasikan sentimen menjadi positif atau negatif. Dengan langkah-langkah yang melibatkan crawling data, preprocessing, pelabelan data otomatis menggunakan InSet Lexicon, pembobotan kata dengan TF-IDF, data splitting, dan klasifikasi dengan algoritma Naïve Bayes. Hasil klasifikasi menunjukkan akurasi sebesar 79.7%, dengan presisi 78.6%, recall 74.0%, dan F1 score 76.2%. algoritma Naïve Bayes mengklasifikasikan sebanyak 1.093 data. Dari hasil tersebut, 453 sentimen positif (41.4%) sementara 640 sentimen negatif (58.6%) berdasarkan data testing sebanyak 20%.
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