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p-Index From 2021 - 2026
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All Journal AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal
Made Marshall Vira Deva
Telkom University
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance

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Sentiment Analysis of Fintech Application Users in Indonesia Using Machine Learning Algorithms Made Marshall Vira Deva; Lukman Abdurrahman; Hanif Fakhrurroja
Acceleration, Quantum, Information Technology and Algorithm Journal Vol. 3 No. 1 (2026): VOLUME 3, NO 1: JUNE 2026
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/aqila.v3i1.171

Abstract

This study focuses on Indonesian users' sentiments regarding 9 fintech apps based on their Google Play Store reviews. The rapid growth of the fintech industry in Indonesia makes it crucial to understand user perceptions and satisfaction. Around 2,554 reviews from users of Kredivo, ShopeePay, Dana, GoPay, LinkAja, Bareksa, Flip, Jenius, and OVO were analyzed. The user review text and data were preprocessed using text cleaning, slang normalization, stopword removal, stemming, and the Sastrawi library and were moved through the TF-IDF vectorizer (term frequency-inverse document frequency). The four algorithms were Naive Bayes, Logistic Regression, Support Vector Machine (SVM), and Random Forest. The results showed that SVM (Linear) achieved the best overall balanced performance with an accuracy of 80.23%, precision of 77.79%, recall of 80.23%, and the highest F1-score of 78.53%, outperforming Naive Bayes (accuracy 81.21%, F1-score 78.32%), Logistic Regression (accuracy 80.43%, F1-score 77.81%), and Random Forest (accuracy 78.08%, F1-score 75.81%). While Naive Bayes recorded the highest raw accuracy, SVM was selected as the best model due to its superior F1-score, which provides a more balanced evaluation across all sentiment classes. Machine learning provided a snapshot of the reviews’ sentiments, with 42.4% positive, 51.4% negative, and 6.1% neutral. Kredivo and ShopeePay had the most favorable sentiments of 72.4% and 70.9%. The most salient sentiment indicators include 'bagus' (good) and 'bantu' (help) as top positive classifiers, while 'buruk' (bad) and 'kecewa' (disappointed) emerged as the most prominent negative classifiers, with 'mudah' (easy) and 'cepat' (fast) also strongly associated with positive sentiment. The results of this study give fintech firms a better grasp of user satisfaction, and fintech user positive sentiments.
Deepfake Technology: Ethical Issues and Legal Gaps in Indonesian Cyber Law Made Marshall Vira Deva; irfan venny rahmayanti; Intan Giri Anjani; Sutan Faiz Rasyid; Muharman lubis
Acceleration, Quantum, Information Technology and Algorithm Journal Vol. 3 No. 1 (2026): VOLUME 3, NO 1: JUNE 2026
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/aqila.v3i1.181

Abstract

The rapid advancement of artificial intelligence (AI) has enabled the emergence of deepfake technology, which allows the manipulation of images, audio, and video to produce highly realistic yet fabricated content. In Indonesia, the proliferation of deepfakes poses significant ethical and legal challenges. This study examines the ethical implications of deepfake technology and identifies gaps in Indonesian cyber law, specifically within the Electronic Information and Transactions Law (UU ITE No. 11/2008 as amended by UU No. 19/2019 and UU No. 1/2024), the Pornography Law (UU No. 44/2008), and the Personal Data Protection Law (UU PDP No. 27/2022). Using a normative juridical research method with qualitative analysis of primary legal sources and secondary literature, this study finds that existing Indonesian legislation does not explicitly regulate deepfakes, creating a legal vacuum that leaves victims predominantly women without adequate legal protection. The findings highlight the urgent need for specific regulatory provisions addressing deepfake creation, distribution, and non-consensual intimate imagery (NCII). This paper concludes by proposing recommendations for legislative reform and ethical frameworks to guide both policymakers and technology users in Indonesia.
Co-Authors Fakhrurroja, Hanif Intan Giri Anjani irfan venny rahmayanti Lukman Abdurrahman Muharman Lubis Sutan Faiz Rasyid