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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
Dewa Made Sutha Raditya Mahattama
Universitas Udayana
Computer Science & IT Engineering

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Analisis Sentimen Berbasis Aspek dengan LDA dan IndoBERT pada Ulasan Aplikasi Stockbit Dewa Made Sutha Raditya Mahattama; Gst Ayu Vida Mastrika Giri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 3 (2026): JNATIA Vol. 4, No. 3, Mei 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i03.p09

Abstract

This study aims to analyze sentiment in user reviews of the Stockbit application using a topic modeling approach combined with IndoBERT-based sentiment classification. Aspect extraction was carried out using Latent Dirichlet Allocation (LDA), and the experimental results indicate that selecting five topics (n_components = 5) provides the most optimal representation, as evidenced by a topic coherence score of 0.6191. These five topics reflect semantic structures that are highly relevant to the content of the reviews. For the sentiment classification stage, the IndoBERT-base model achieved an accuracy of 90.86%. The best performance was observed for the positive class, with an F1-score of 93.73%, while the negative class yielded an F1-score of 83.12%. This performance gap is attributed to the imbalanced data distribution, where positive sentiments are more dominant. Nevertheless, the macro-average F1-score of 88.43% demonstrates that the model is still capable of classifying both classes in a relatively balanced manner.
Co-Authors Gst. Ayu Vida Mastrika Giri