(JOSH - S4) - Andriani, Hasan [2025-07-31]

Hasan, Firman Noor (2025) (JOSH - S4) - Andriani, Hasan [2025-07-31]. Analisis Sentiment Ulasan Aplikasi Riliv di Google Playstore dengan Algoritma SVM, 6 (4). pp. 2307-2315. ISSN 2686-228X

	Text 1. Cover.pdf Download (79kB)
	Text 2. Editorial Team.pdf Download (287kB)
	Text 3. Daftar Isi.pdf Download (5MB)
	Text 4. Artikel.pdf Download (442kB)
	Text 5. Bukti Hasil Turnitin.pdf Download (716kB)
	Text 6. LOA - Andriani, Hasan.pdf Download (62kB)
	Image Bukti Korespondensi - 1.jpeg Download (70kB)

Abstract

his study aims to conduct sentiment analysis on user reviews of the Riliv: Mental Health App on Google Play Store using the Support Vector Machine (SVM) algorithm. The analysis process includes review data collection via web scraping, text cleaning using text preprocessing, automatic labeling based on rating scores, data transformation using the TF-IDF method, data splitting with Stratified K-Fold Cross Validation, SVM model training, and performance evaluation. The dataset comprises 2,000 reviews with an imbalanced label distribution: positive (75,3%), netral (5,3%), and negative (19,4%). The classification results show that the SVM model achieved an accuracy of 85.56%. It performed well in identifying positive sentiment with an f1-score of 0.96 and negative sentiment with 0.69. However, the model failed to classify neutral sentiment due to the small number of data, which was insufficient for meaningful pattern recognition. Evaluation and visualization results indicate that label imbalance is a major challenge. Therefore, additional strategies such as data balancing, class weighting, or the use of alternative algorithms are necessary. This research is expected to serve as a foundation for developing a more accurate and fair sentiment analysis system across all sentiment categories in the context of digital mental health services.

Item Type:	Article
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Teknik Informatika
Depositing User:	Mr Firman Noor Hasan
Date Deposited:	11 Nov 2025 03:58
Last Modified:	11 Nov 2025 03:58
URI:	http://repository.uhamka.ac.id/id/eprint/48458

Actions (login required)

View Item