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All Journal Journal of Information Systems and Informatics Journal of Information System and Artificial Intelligence
Putri Taqwa Prasetyaningrum
Mercu Buana University Yogyakarta
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Comparative Analysis of Machine Learning Algorithms for Sentiment Classification of Discord App Reviews Rani Rosita; Putri Taqwa Prasetyaningrum
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1367

Abstract

The increasing use of digital communication applications such as Discord has generated diverse user opinions expressed through reviews on the Google Play Store. This study aims to analyze user sentiment toward the Discord application using text mining and machine learning techniques. A total of 3,000 reviews were collected through web scraping, pre-processed, labeled using a lexicon-based approach with TextBlob, and balanced using the SMOTE-Tomek method. Sentiment classification was performed into positive, negative, and neutral categories using Decision Tree, Logistic Regression, Support Vector Machine (SVM), and an Ensemble method. The Ensemble model achieved the highest accuracy of 98.67%, followed by Decision Tree (96.50%), SVM (95.83%), and Logistic Regression (90.33%). Limitations of this study include the use of lexicon-based sentiment labeling, machine translation from Indonesian to English, and initial class imbalance. Despite this strong performance, the study has limitations related to lexicon-based labeling, translation of reviews into English, and the presence of a highly imbalanced class distribution in the original dataset. Overall, the findings demonstrate that the Ensemble approach effectively improves sentiment classification accuracy and can support data-driven decision-making in application development.
Implementation of Enterprise Resource Planning at Chic Boutique Fashion Store Hildegardis Kristina Saka; Putri Taqwa Prasetyaningrum
Journal of Information System and Artificial Intelligence Vol. 7 No. 1 (2026): Vol.7 No. 1 (2026): Journal of Information System and Artificial Intelligence V
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jisai.v7i1.246

Abstract

In this era filled with many digital-based activities, it indirectly encourages business people to move out of their comfort zone. One of them is the Chic Boutique Fashion Store. The Chic Boutique Fashion Clothes Store is a clothing store that focuses on selling various types of trendy and quality clothing. Chic Boutique has marketed its products online. However, this has not been considered effective because several work systems such as making billing receipts, cashiers, official Seller websites, have not used an adequate ERP system. Therefore, in this study, the application that can overcome the problems that occur is the Odoo ERP application. Odoo is an open source ERP application that can be accessed via a website, which is suitable for use in new companies so that it can reduce costs for the application development process. The modules developed at the Chic Boutique Fashion Store include the Point of Sale Module, Website Module, Invoicing Module, Inventory Module, and Contacts Module
Co-Authors Hildegardis Kristina Saka Rani Rosita