Implementasi Web Tool Analisis Sentimen Ulasan Aplikasi Google Play Store Menggunakan Logistic Regression

Ahmadi, Asad Nirot and , Devi Afriyantari Puspa Putri, S.Kom., M.Sc. (2026) Implementasi Web Tool Analisis Sentimen Ulasan Aplikasi Google Play Store Menggunakan Logistic Regression. Skripsi thesis, Universitas Muhammadiyah Surakarta.

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Abstract

The rapid growth of apps on the Google Play Store has resulted in a large volume of user reviews, making it difficult to analyze them manually—even though these reviews contain important information for evaluating app quality and user satisfaction. This study aims to design a web-based sentiment analysis system capable of automatically classifying reviews into positive and negative sentiments. A total of 20,000 reviews were collected via web scraping using Application IDs, followed by manual labeling and preprocessing that included case folding, text normalization, and text cleaning. The system was built using the Logistic Regression algorithm and applied TF-IDF for feature extraction, with a training-to-test data ratio of 90:10. To improve classification accuracy for the positive class, a classification threshold of 0.6 was applied. Based on the test results, the model achieved an accuracy of 97.70%, while evaluation using Repeated Stratified K-Fold Cross-Validation yielded an average F1-score of 89.47%, indicating the model’s performance stability across various data partitioning schemes. The resulting model was successfully implemented into a web-based system, enabling it to automatically perform sentiment analysis on Google Play Store app reviews.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	google play store, sentiment analysis, logistic regression, TF-IDF
Subjects:	T Technology > Information Technology > Artificial Intelligence T Technology > Information Technology > Software. Aplication > Pemograman T Technology > Information Technology > Software. Aplication > Software Engineering Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Divisions:	Fakultas Komunikasi dan Informatika > S1 Teknik Informatika
Depositing User:	AS'AD NIROT AHMADI
Date Deposited:	07 Aug 2026 07:04
Last Modified:	07 Aug 2026 07:04
URI:	http://eprints.ums.ac.id/id/eprint/147068

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