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All Journal Jurnal Accounting Information System (AIMS)
Setiana, Elia Setiana
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Computer Science & IT Economics, Econometrics & Finance Education Other

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Analisis Sentimen Aplikasi BYOND by BSI di Google Play Store Menggunakan Metode SVM Akbar, Imannudin; Sinaga, Arnold Ropen Sinaga; Yoga, Titan Parama; Hendra, Acep; Setiana, Elia Setiana
Jurnal Accounting Information System (AIMS) Vol. 8 No. 2 (2025)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v8i2.1583

Abstract

The BYOND by BSI application has received various user reviews on the Google Play Store, reflecting user perceptions and satisfaction. Sentiment analysis is needed to understand these opinion patterns and support service quality improvement. This study aims to analyze the sentiment of BYOND by BSI user reviews by applying the Support Vector Machine (SVM) method. Review data were collected from the Google Play Store and processed through text preprocessing stages followed by SVM classification modeling. The results show a classification accuracy of 87%, with strong performance in the Positive class (F1-score 0.91) and Negative class (F1-score 0.88), but SVM failed to detect the Neutral class due to data imbalance, where the Neutral class accounted for only 5.85% of the total samples. In conclusion, these findings highlight the importance of handling class imbalance through approaches such as resampling, ensemble algorithms, or class-weight optimization in SVM to improve the accuracy of Neutral sentiment detection.
Co-Authors Acep Hendra Akbar, Imannudin Sinaga, Arnold Ropen Sinaga Titan Parama Yoga