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All Journal Jurnal ULTIMATICS
Elham Syahrian Putra
Universitas Sebelas Maret
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Automated Vader Lexicon Labeling on Sentiment Analysis Against The E-Wallet Febri Liantoni; Muhammad Hardiansyah; Elham Syahrian Putra; Erna Piantari
ULTIMATICS Vol 18 No 1 (2026): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v18i1.4536

Abstract

In Indonesia, e-wallets have gained immense popularity due to their user-friendly interfaces and attractive features. Despite their convenience, user opinions about e-wallet applications remain polarized, with sentiments ranging from highly positive to critically negative. This study seeks to analyze these diverse user sentiments by leveraging the VADER Lexicon model, a powerful tool for sentiment analysis. The Naïve Bayes Classifier, a well-established probabilistic model renowned for its efficacy in text-based classification tasks, is employed to categorize user reviews. The sentiment analysis yielded promising results, with the model achieving an impressive accuracy rate of 92.02%. Additionally, the precision of the model, indicating the ratio of correctly predicted positive sentiments to all predicted positive sentiments, stood at 83.23%. The recall, representing the ratio of correctly predicted positive sentiments to all actual positive sentiments, was recorded at 86.80%. These metrics underscore the model's robustness in accurately classifying user sentiments. The insights gained from this analysis provide a deeper understanding of user perspectives, aiding in the evaluation and enhancement of e-wallet applications.
Co-Authors Erna Piantari Febri Liantoni Muhammad Hardiansyah