Vol. 1 No. 1 (2020): RESOLUSI September 2020

Penerapan Algoritma Naive Bayes Classifier Untuk Mendeteksi Tingkat Krediblitas Hoax News/ Fake News Pada Sosial Media Di Indonesia Berbasis Android (Studi Kasus : Kantor Tribun Medan)

M. Ibrahim (Universitas Budi Darma)
Efori Bu'ulolo (Universitas Budi Darma)
Ikwan Lubis (Universitas Budi Darma)

Article Info

Publish Date
20 Sep 2020


The hoax is the most massive problem in Indonesia that requires more attention from the government and elements of society. People who easily receive hoax news from information that is disseminated instantly change their mindset and emotional feelings towards the contents of news that contain hate speech. The government is trying to prevent and oversee every hoax news disseminator, and will even give penalties to hoax spreaders. The reason is that hoax news only harms and gives a bad reputation to others for the delivery of incorrect information. To prevent this, a grouping of data is made to detect the level of accuracy of the news disseminated by the Naive Bayes classifier method in Android-based. This method was chosen in addition to new developments in spam filtering programming, it also has a higher level of accuracy.

Copyrights © 2020

Journal Info





Computer Science & IT


Resolusi : Rekayasa Teknik Informatika dan Informasi, membahas ilmu dibidang Informatika, Sistem Informasi, Manajemen Informatika, DSS, AI, ES, Jaringan, sebagai wadah dalam menuangkan hasil penelitian baik secara konseptual maupun teknis yang berkaitan dengan Teknologi Informatika dan Komputer. ...