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All Journal Traksi : Majalah Ilmiah Teknik Mesin Journal Of Artificial Intelligence And Software Engineering
Aditya, Ari
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Computer Science & IT Energy Engineering

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Journal : Journal Of Artificial Intelligence And Software Engineering

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Sentiment Analysis of Quizizz Application User Reviews Using Logistic Regression Algorithm Aditya, Ari; Tresnawati, Shandy
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7292

Abstract

Digital learning applications like Quizizz are increasingly popular for offering interactive learning experiences. As user numbers grow, so do the reviews on platforms like Google Play Store, reflecting user perceptions of app quality. This study aims to analyze user review sentiment toward the Quizizz application using the Logistic Regression algorithm. The data consists of Indonesian-language reviews collected from March to December 2024. The analysis process includes text preprocessing using the Sastrawi library, lexicon-based sentiment labeling, TF-IDF weighting, and classification using Logistic Regression. The model is evaluated using accuracy, precision, recall, and f1-score. The results show that most reviews are positive, and the model performs well in sentiment classification. These findings offer insights for developers to improve the app’s quality and user experience.
Co-Authors Tresnawati, Shandy