Article Per Year (5 Year)
p-Index From 2021 - 2026
1.704
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Indonesian Journal of Artificial Intelligence and Data Mining JISTECH: Journal of Information Science and Technology
Julius Panda Putra Naibaho
Universitas Papua
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Classification of Online Gambling Spam Comments on YouTube Using Support Vector Machine Umbu Anaagung Pariamalinya; Josua Josen A. Limbong; Julius Panda Putra Naibaho
Indonesian Journal of Artificial Intelligence and Data Mining Vol. 9 No. 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

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

Abstract

While digital transformation has established YouTube as a major communication platform, the site has also become vulnerable to online gambling spam in Indonesia. This study investigates the effectiveness of the Support Vector Machine (SVM) algorithm for automated spam detection as an alternative to manual moderation. A total of 9,169 comments were collected from gaming, education, and entertainment channels using the YouTube Data API v3 and were used to train and evaluate the model with an 80:20 data split. The experimental results show that SVM achieved an accuracy of 99.62% and an F1-score of 0.996, demonstrating strong capability in identifying spam comments written in informal and modified promotional language. The main contribution of this study is the development of a highly accurate and practical spam detection approach for Indonesian YouTube comments, which can support more efficient moderation systems. However, the model still has limitations in detecting sarcastic content. Therefore, future research should explore deep learning models such as BERT to improve contextual understanding and strengthen automated moderation in digital environments.
Co-Authors Alex De Kweldju Alfi Syahriza Andreas Sumendap Ari Nur Safitri Prameti Ningsih Ari_Fadli La Tardi cindy aprillia atmaja Isaiah Carlietias Kusuma Wanal Yom Josua Josen A. Limbong Lion Ferdinand Marini Lion Ferdinand Marini Marlinda Sanglise Nur Jamila Regina Natalia Sianturi Ridho Nur Fauzi Umbu Anaagung Pariamalinya Wahyu Akbar Yosia Artahsasta