Lewati ke konten utama
JOURNAL ARTICLE

Jurnal Institusi

Copyright (c) 2025 ComniTech : Journal of Computational Intelligence and Informatics

Sentiment Analysis Of Halodoc Application User Satisfaction Using The Naïve Bayes Method, SVM and LSTM

The growth of digital technology in the health sector has encouraged the emergence of various health service applications, one of which is Halodoc. This study aims to analyze the sentiment of user satisfaction with the Halodoc application through reviews left on the Google Play Store. The method used in this research is Naïve Bayes, with stages including data collection, preprocessing (case folding, cleansing, tokenizing, stopword removal, stemming), weighting using TF-IDF, and sentiment classification. This research uses 350 review data as a dataset. The evaluation results showed that the Naïve Bayes-based sentiment classification model achieved 84% accuracy, with the majority of user sentiments being positive. The findings illustrate that the Halodoc application is generally well received by its users, but still needs improvement in some aspects of the service.

Informasi Detail
Journal
ComniTech : Journal of Computational Intelligence and Informatics ; Vol. 2 No. 1 (2025): ComniTech : Journal of Computational Intelligence and Informatics; 14-23
Penerbit
Universitas Lancang Kuning
Tahun Terbit
Bahasa
eng
ISSN
-
License
Copyright (c) 2025 ComniTech : Journal of Computational Intelligence and Informatics
Last Updated
2025-08-03T08:03:33Z
Info Journal

ComniTech : Journal of Computational Intelligence and Informatics ; Vol. 2 No. 1 (2025): ComniTech : Journal of Computational Intelligence and Informatics; 14-23

Penerbit: Universitas Lancang Kuning