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Lexicon-enhanced aspect-based sentiment analysis for evaluating Indonesian learning applications Wibowo, Jonathan Arya; Lubis, Muharman; Utomo, Rio Guntur; Ladkoom, Kobthong
Indonesian Research Journal in Education |IRJE| Vol. 10 No. 3 (2026): IRJE |Indonesian Research Journal in Education| in Progress|
Publisher : Universitas Jambi, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/irje.v10i3.55965

Abstract

This study evaluates user perceptions of two Indonesian learning applications, Ruangguru and Pahamify, through lexicon-enhanced aspect-based sentiment analysis of 14,768 Google Play reviews published between 2020 and 2025. EduAppLex-ID, a pilot domain lexicon containing 46 multiword expressions, was developed as an extension of the Indonesian Sentiment Lexicon. Overall sentiment toward both applications was favorable, with Pahamify showing a small but statistically significant advantage. Pedagogical quality received the most positive evaluation, whereas system quality was evaluated negatively for both applications. Monetization produced the largest difference between the applications. A lexicon audit identified eighteen high-frequency entries whose polarity assignments were unsuitable for the educational-application domain. These entries accounted for approximately one-fifth of the corpus’s sentiment mass, and their removal increased the observed between-application effect size. Because no human-annotated validation dataset was available, interpret the findings as exploratory evidence. The results demonstrate the importance of domain-specific lexicon calibration and aspect-level analysis when examining Indonesian educational-application reviews.