Hoax Classification Using Naïve Bayes Algorithm

  • Riana Pramesti Putri Universitas Udayana
  • Ngurah Agus Sanjaya ER Universitas Udayana


The use of social media which is so mushrooming today, has many positive impacts but does not cover the negative impacts, one of which is the misuse of information. Hoax is one of the causes of disinformation and public unrest. The speed of spread, which sometimes cannot be controlled, is one of the reasons why hoax news is still being spread every day. Therefore, it is necessary to classify hoax news with the aim of helping the public in separating the news that is being spread. This study uses the Naive Bayes algorithm as a classification model with the addition of hyperparameter tuning. The best model is produced with an alpha of 0.01 which has an accuracy of 87.9%.

How to Cite
PUTRI, Riana Pramesti; SANJAYA ER, Ngurah Agus. Hoax Classification Using Naïve Bayes Algorithm. Jurnal Nasional Teknologi Informasi dan Aplikasinya (JNATIA), [S.l.], v. 1, n. 1, p. 181-186, nov. 2022. Available at: <https://ojs.unud.ac.id/index.php/jnatia/article/view/92596>. Date accessed: 27 jan. 2023.

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.