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All Journal Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam
Putri Inombi, Syindikha
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Mathematics Physics

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Analisis Sentimen Pengguna X (Twitter) Terhadap Kebijakan Tapera Di Indonesia Menggunakan Metode CNN Dan BERT Putri Inombi, Syindikha; Rahmawaty Isa, Dewi; Asriadi; K. Nasib, Salmun; K. Hasan, Isran; Nurmardia Abdussamad, Siti
Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 6 No. 2 (2025): Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : Cahaya Ilmu Bangsa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3483/trigonometri.v6i2.12267

Abstract

The government’s Housing Savings Program (TAPERA) has sparked various public reactions, particularly on social media platform X (Twitter). This study aims to analyze user sentiment toward the TAPERA policy using the Convolutional Neural Network (CNN) and Bidirectional Encoder Representations from Transformers (BERT) methods. The dataset was collected using a crawling technique on X (Twitter), comprising a total of 1,790 tweets. These data were processed through preprocessing stages, including cleaning, case folding, normalization, tokenization, stopword removal, and stemming. The CNN and BERT models were then trained and tested to classify sentiments as positive or negative. The findings indicate that the BERT model outperformed CNN, achieving a higher accuracy of 86% compared to CNN’s 85%, along with superior recall, precision, and F1-score values. These results suggest that the BERT method is more effective in comprehensively understanding sentiment context.
Co-Authors Asriadi K. Hasan, Isran K. Nasib, Salmun Nurmardia Abdussamad, Siti Rahmawaty Isa, Dewi