Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Horizon: Indonesian Journal of Multidisciplinary
firlana eza putra firlana
Universitas Bhinneka PGRI
Agriculture, Biological Sciences & Forestry Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Social Sciences Other

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

Found 1 Documents
Search

 1 
Analisis Sentimen Sikap Publik terhadap Konten Deepfake di Tiktok melalui Model Deep Learning Indobert firlana eza putra firlana; Yayak Kartika Sari; Taufiq Agung Cahyono
HORIZON: Indonesian Journal of Multidisciplinary Vol. 4 No. 3 (2026): HORIZON: Indonesian Journal of Multidisciplinary
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/zmrpnq33

Abstract

Abstract. The rapid advancement of artificial intelligence has enabled the creation of deepfake content that is increasingly realistic and difficult to distinguish from authentic media. The widespread dissemination of deepfakes on social media, particularly TikTok, has generated diverse public responses due to risks of misinformation, opinion manipulation, and ethical concerns. As one of the most popular platforms in Indonesia, TikTok provides a space for public opinion through user comments. This study aims to analyze public sentiment toward deepfake content on TikTok using a deep learning approach based on the IndoBERT model. The dataset consists of 4,000 Indonesian-language comments collected through web scraping using deepfake-related keywords. Sentiment labeling was conducted using a lexicon-based approach and classified into positive, neutral, and negative categories. The research process includes text preprocessing, data splitting, and IndoBERT fine-tuning. Model performance is evaluated using accuracy, precision, recall, and F1-score. The results show that negative sentiment dominates, indicating public concern over potential misuse of deepfake technology. This study provides insights for policymakers and platform stakeholders.
Co-Authors Sari, Yayak Kartika Taufiq Agung Cahyono