Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of Technology and Computer (JOTECHCOM)
Siregar, Kiki Putriani
Unknown Affiliation
Computer Science & IT

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

Found 1 Documents
Search

 1 
Text Classification Using TF-IDF and Naïve Bayes: Case Study of MyXL App User Review Data Nurhayati, Nurhayati; Hartimar, Lima; Manza, Yuke; Siregar, Kiki Putriani
Journal of Technology and Computer Vol. 2 No. 2 (2025): May 2025 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The MyXL application, developed by leading Indonesian operator XL Axiata, allows customers to independently manage their telecommunication services. However, a significant volume of negative user reviews necessitates a deeper analysis of user sentiment. This research classifies MyXL app reviews using the TF-IDF (Term Frequency-Inverse Document Frequency) method for feature extraction and the Naïve Bayes algorithm for sentiment classification, implemented via a Python-based GUI. The study's objective is to categorize reviews into positive, negative, and neutral sentiments. A dataset of 1000 user reviews from Kaggle underwent comprehensive preprocessing—including text cleaning, normalization, tokenization, stopword removal, and stemming—before conversion into a numerical representation using TF-IDF. The classification model, built with the Naïve Bayes algorithm, was evaluated using accuracy, precision, recall, and F1-score metrics. The model achieved an accuracy of 61.5%. This finding demonstrates that combining TF-IDF and Naïve Bayes is effective for classifying sentiment in Indonesian text reviews, particularly within the mobile app domain. Furthermore, the methodology shows clear potential for development into a large-scale and automated user opinion analysis system.
Co-Authors Hartimar, Lima Manza, Yuke Nurhayati Nurhayati