Detection of Hoax News Using TF-IDF Vectorizer and Multinomial Naïve Bayes and Passive Aggressive - Adrian, Rizky; Musaddam; Ikhsan, Muhammad; Pahlevi. B, M. Riza (MASE - Media Applied and Engineering, 2024)
The website is a source of information, but not all information is guaranteed to be correct. Some news can beconsidered hoaxes or not based on facts. This research aims to build a hoax news detection system on English languagenews websites. The method used involves the multinomial Naive Bayes and Passive Aggressive approaches.Classification report analysis shows the superiority of the Passive Aggressive Classifier with significant improvementsin all evaluation metrics compared to Multinomial Naïve Bayes. The conclusion is based on the characteristics of thedataset, confirming the effectiveness of the Passive Aggressive Classifier in solving the task of classifying fake news inEnglish, with the highest accuracy reaching 93.74%.