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All Journal The Indonesian Journal of Computer Science
Ramaputra, Chrisdion Andrew
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Analisis Sentimen Ulasan Pengguna pada Aplikasi Cryptocurrency: Evaluasi Dampak Skenario Pembagian Dataset Menggunakan Multinomial Naive Bayes Ramaputra, Chrisdion Andrew; Al Faroby, Mohammad Hamim Zajuli; Lidiawaty, Berlian Rahmy
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4263

Abstract

The surge in cryptocurrency investors in Indonesia, reaching 18.83 million by January 2024, signifies an expanding interest in this market. This research conducts a sentiment analysis of user reviews on Indodax and Tokocrypto, the premier cryptocurrency trading platforms in Indonesia. Utilizing the Multinomial Naive Bayes method, the study examines the influence of various dataset split scenarios and random states on the model's performance. The findings reveal substantial variability in the model's accuracy based on different random states and test sizes. Notably, the Positive sentiment label consistently shows high-performance metrics, while the Neutral label underperforms. These insights are invaluable for developers aiming to improve user experience and for investors seeking to make informed decisions. This research underscores the significance of sentiment analysis in understanding user interactions and enhancing the credibility of cryptocurrency investment platforms.
Co-Authors Berlian Rahmy Lidiawaty Mohammad Hamim Zajuli Al Faroby