Mohd Yusof, Ahmad Faisal Daniell and Zainuddin, Aiman Kamal and Hassan, Raini (2026) Berita Debunked: real-time fake news detection and alert system. International Journal on Perceptive and Cognitive Computing, 12 (1). pp. 74-80. E-ISSN 2462-229X
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Abstract
BeritaDebunked is an AI-driven near real-time fake news detection and alert system designed to combat misinformation in Malaysia, particularly on platforms such as WhatsApp. The system combines natural language processing and multimodal deep learning by using BERT for textual analysis and BLIP-2 for image–text evaluation. Deployed as a browser extension, it flags suspicious messages and allows continuous model updates through a scalable backend. Evaluation on the Fakeddit benchmark dataset demonstrates that the proposed hybrid architecture achieves an accuracy of (83.3%), with a precision of (82.6%) and an F1-score of (84.9)%. While unimodal text baselines achieved marginally lower raw accuracy (82.9%), the hybrid model demonstrates superior robustness in detecting multimodal context mismatches. The system demonstrates real-time capability with an average inference latency of 56.42 ms. By enabling timely detection and user-friendly alerts, BeritaDebunked aims to support digital literacy efforts, reduce the spread of misinformation, and contribute to Sustainable Development Goal 16 by strengthening information integrity
| Item Type: | Article (Journal) |
|---|---|
| Uncontrolled Keywords: | Hybrid, Fake news, SDG 16, BERT, BLIP-2, Multimodal deep learning, NLP |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science |
| Depositing User: | Dr. Raini Hassan |
| Date Deposited: | 10 Feb 2026 16:05 |
| Last Modified: | 10 Feb 2026 16:05 |
| Queue Number: | 2026-02-Q2106 |
| URI: | http://irep.iium.edu.my/id/eprint/127384 |
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