Pemanfaatan Metode Klasifikasi Naïve Bayes Untuk Pendeteksi Berita Hoax Pada Artikel Berbahasa Indonesia
DOI:
https://doi.org/10.24014/coreit.v7i2.14290Abstract
Berita hoax sudah sangat banyak tersebar di internet. Kemudahan dalam membuat dan membagikan merupakan salah satu faktornya. Berita hoax menjadi ancaman dan konsentrasi banyak pihak, muncul masalah dalam mengidentifikasi atau mengklasifikasikannya karena tidak ada pola yang dapat diidentifikasikan, serta gaya penulisan bersifat bebas dan tidak kaku. Kurang akuratnya sistem deteksi hoax yang ada diakibatkan belum ditemukannya metode dan atribut yang digunakan untuk klasifikasi berita hoax dengan akurasi yang tinggi. Atas dasar itulah penelitian ini dilakukan, seperti pada kebanyakan klasifikasi berita hoax yang dijadikan acuan pada penelitian ini, dilakukan praproses (case folding, tokenisasi, stemming dan stopword removal), ekstrasi fitur dan penambahan atribut selain dari praproses artikel seperti website tempat artikel di publikasi dan status website tersebut. Hasil dari penelitian ini didapatkan akurasi sebesar 72% yang ternyata terjadi penurunan 6.6% dibandingkan dengan penelitian sebelumnya yang sebesar 78.6% dikarenakan satu website yang hanya mempublikasi satu artikel hoax dan dibiarkan domain website tersebut expired, dengan begitu terjadi pengurangan terhadap bobot nilai klasifikasi.
Kata Kunci : Artikel Hoax, klasifikasi, Naïve Bayes, Union.
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