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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Amanda Tabitha Bulan Panjaitan
Politeknik Statistika STIS
Computer Science & IT Control & Systems Engineering

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Transfer Learning of Pre-trained Transformers for Covid-19 Hoax Detection in Indonesian Language Lya Hulliyyatus Suadaa; Ibnu Santoso; Amanda Tabitha Bulan Panjaitan
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 15, No 3 (2021): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.66205

Abstract

Nowadays, internet has become the most popular source of news. However, the validity of the online news articles is difficult to assess, whether it is a fact or a hoax. Hoaxes related to Covid-19 brought a problematic effect to human life. An accurate hoax detection system is important to filter abundant information on the internet.  In this research, a Covid-19 hoax detection system was proposed by transfer learning of pre-trained transformer models. Fine-tuned original pre-trained BERT, multilingual pre-trained mBERT, and monolingual pre-trained IndoBERT were used to solve the classification task in the hoax detection system. Based on the experimental results, fine-tuned IndoBERT models trained on monolingual Indonesian corpus outperform fine-tuned original and multilingual BERT with uncased versions. However, the fine-tuned mBERT cased model trained on a larger corpus achieved the best performance.
Co-Authors Ibnu Santoso Suadaa, Lya Hulliyyatus