DOI: https://doi.org/10.14710/lenpust.v12i1.77424

Sentiment Analysis of User Reviews of the iPusnas on the Google Play Store Using the Orange Platform

*Rezi Anjelia Putri orcid  -  Library and Information Science, Universitas Indonesia, Depok, Indonesia, Indonesia
Muhamad Prabu Wibowo orcid  -  Library and Information Science, Universitas Indonesia, Depok, Indonesia, Indonesia
Received: 31 Aug 2025; Revised: 18 Apr 2026; Accepted: 7 May 2026; Published: 30 Jun 2026.

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Abstract

Background: Digital library applications have expanded access to reading materials, making user experience an important dimension of service evaluation. iPusnas, developed by the National Library of Indonesia, has attracted substantial user engagement, reflected in the large number of reviews on the Google Play Store. These reviews provide valuable insights into public perception yet require systematic analysis to inform service improvement.

Objective: This study aims to examine user sentiment and emotional tendencies toward the iPusnas application based on Google Play Store reviews, with the goal of identifying key aspects of user experience that require attention.

Methods: This study applies a sentiment analysis approach to 500 user reviews collected through data scraping between 2024 and May 2025. The analysis involves text preprocessing, sentiment classification, and emotion detection using the SentiArt lexicon-based method, which enables the identification of affective dimensions in textual data. Model performance is evaluated using precision and recall metrics, and results are further explored through word frequency and topic patterns.

Results: The findings show that positive sentiment is primarily associated with expressions of satisfaction and enjoyment, while negative sentiment reflects frustration related to technical issues and service limitations. The classification model demonstrates relatively high precision for both positive (84.4%) and negative (94.7%) categories, but lower recall, indicating limitations in capturing diverse expressions of sentiment in Indonesian-language reviews. Thematic patterns highlight recurring concerns such as application stability, access to collections, and user interface experience.

Conclusion: User reviews of iPusnas reveal a combination of positive engagement and persistent technical concerns. The results suggest that sentiment analysis can support service evaluation but also highlight methodological challenges in accurately capturing nuanced expressions in Indonesian. Strengthening system performance and responsiveness to user feedback remains essential to enhancing the role of iPusnas in supporting digital literacy

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Keywords: IPusnas, sentiment analysis; orange; user reviews; digital library application

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