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All Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Frans Mikael Sinaga
Department of Informatics, Universitas Mikroskil, Indonesia
Computer Science & IT Education Engineering

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Sentiment Analysis of Sirekap Election Using BERT on Big Data from X (formerly Twitter) in Indonesia Sunaryo Winardi; Sio Jurnalis Pipin; Heru Kurniawan; Frans Mikael Sinaga; Dela Amelia Sitorus; Devi Putriani Sinaga
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 15 No. 1 (2026)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v15i1.84741

Abstract

This study explores the use of the BERT model for sentiment analysis of the SIREKAP system, focusing on preprocessing and model optimization. Lexicon-based sentiment labeling revealed that 8% of the data was positive, 85.1% negative, and 6.9% neutral. These results were refined through manual evaluations by two judges, integrated with lexicon-based labels using majority voting. To address class imbalance, SMOTE was applied, leading to notable performance improvements. The BERT model's accuracy showed substantial enhancement after SMOTE was implemented. A lower learning rate of 1×10⁻⁵ consistently produced strong results, especially with larger batch sizes. The highest average accuracy of 98.9% was achieved at epoch 1 with a learning rate of 2.5×10⁻⁵ and a batch size of 8. This result indicates a significant improvement in model performance compared to initial results.
Co-Authors Dela Amelia Sitorus Devi Putriani Sinaga Heru Kurniawan Sio Jurnalis Pipin Sunaryo Winardi