Hoax Classification Using Naïve Bayes Algorithm
Abstract
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%.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
