Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Nevrada, Nofsa Atia
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sentiment Analysis of Telegram App Reviews on Google Play Store Using the Support Vector Machine (SVM) Algorithm Nevrada, Nofsa Atia; Syaputra, Muhammad Adie
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8851

Abstract

This study aims to analyze the sentiment of Telegram application reviews on the Google Play Store using the Support Vector Machine (SVM) algorithm. From a total of 14,700,000 initial reviews, a sampling technique was carried out to obtain 400 review data, which then went through the pre-processing stage to produce 345 review data to be classified. The SVM model used showed good performance with an accuracy of 81.16%, precision in the positive class reached 93%, recall in the negative class of 94%, and an average f1-score of around 81%. However, there was a discrepancy between the high rating and the content of the review, which highlighted the existence of high-rated reviews that contained criticism or vice versa. The confusion matrix analysis also showed some misclassification, where reviews should be categorized as positive sentiment but detected as negative, and vice versa. This research is expected to provide valuable feedback for Telegram application developers to improve the quality of service, although the results of this analysis have not been fully discussed in practice. The limitation of this study is that it only tested reviews that used Indonesian, which limited the scope of the findings to the context of local users.
Co-Authors Syaputra, Muhammad Adie