Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Innotech
Tiarma Sipahutar, Angel
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
KLASIFIKASI BERITA HOAX POLITIK PADA MEDIA SOSIAL X MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN RANDOM FOREST Astuti, Rika; Tiarma Sipahutar, Angel
Innotech: Jurnal Ilmu Komputer, Sistem Informasi dan Teknologi Informasi Vol 2 No 1 (2025): Innotech Issue Januari 2025
Publisher : Universitas Siber Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Social media has become a major source of information as well as a fertile ground for the spread of hoax news, particularly political news. This study examines two classification algorithms, Naive Bayes and Random Forest, to detect hoax news. The data used consists of political news labelled as hoax or non-hoax. The results show that the Random Forest algorithm has better accuracy and performance compared to Naive Bayes in terms of precision, recall, and F1-score. In conclusion, Random Forest is more effective for classifying political hoax news on social media. This research provides important insights into the application of machine learning algorithms in text classification and emphasizes the importance of selecting the right algorithm for optimal results.
Co-Authors Rika Astuti