Klasifikasi Hoaks Menggunakan Metode Maximum Entropy Dengan Seleksi Fitur Information Gain

Albert Bill Alroy (Fakultas Ilmu Komputer, Universitas Brawijaya)
Putra Pandu Adikara (Fakultas Ilmu Komputer, Universitas Brawijaya)
Sigit Adinugroho (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 3 No 9 (2019): September 2019

In 2016, Indonesia has 132 million internet users. This number increase to 143 million users in 2017. Internet user can access many things such as chatting services, social media, and e-commerce. There are many people who intentionally make false information known as Hoax. Hoax are information or news that contains uncertain facts or events that have not occured. The problem of spreading Hoax can be reduced by making a system that can classify whether a news is a Hoax or not. The method used in this research is Maximum Entropy with Information Gain Fiture Selection. The amount of data used in this research is 600 articles in Indonesian. There are 372 news articles classified as facts and 228 news articles classifed as Hoax. The amount of best results accuracy in this research is 0,8 with information information gain fiture selection (threshold = 50%), 1 precision, 0,8 recall, and 0,89 f-measure.