Sistem Identifikasi "Fake News" menggunakan Metode Multinomial Naïve Bayes
DOI:
https://doi.org/10.26418/justin.v10i4.52441Keywords:
Analisis, Multninomial Naïve Bayes, Berita Hoaks, Twitter APIAbstract
Penyebaran berita melalui media sosial sangat cepat di masa kini. Tidak hanya melalui televisi tetapi kini dapat ditemukan di berbagai platform seperti platform global yaitu twitter. Tetapi dengan cepatnya penyebaran tidak memungkiri berita palsu atau yang dikenal sebagai hoaks marak muncul ke permukaan. Dengan berbagai tujuan dari pengunggahnya, berita hoaks dapat menyebabkan perpecahan di antara masyarakat dan juga misinformasi. Melalui uji coba yang dilakukan berita dapat diklasifikasikan sebagai berita actual atau hoaks dengan menggunakan metode Multinomial Naïve Bayes, yaitu algoritma yang biasa digunakan untuk klasifikasi data/teks pada kelas tertentu. Data didapatkan melalui proses crawling data Twitter API dengan query "berita" sebanyak 500 di preprocessing dan dilabeling sebelum ditrain dan menjadi data test. Setelah melakukan uji coba, akurasi model yang didapatkan menggunakan algoritma ini sebesar 83 % dan akurasi training set sebesar 94 %.
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