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All Journal Jurnal Informatika Dan Tekonologi Komputer
Indra Dikusuma
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Computer Science & IT Control & Systems Engineering Other

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Perbandingan Naïve Bayes dan Logistic Regression untuk Analisis Sentimen Ulasan Produk Skincare di Tokopedia Indra Dikusuma; Yunus Widjaja
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i3.8420

Abstract

This study aims to compare the performance of Naïve Bayes (NB) and Logistic Regression (LR) in classifying the sentiment of skincare product reviews on Tokopedia. A total of 973 reviews were collected and processed through text preprocessing and feature extraction using TF-IDF. Evaluation using accuracy, precision, recall, and F1-score showed that NB achieved an accuracy of 75.9% but struggled to detect negative sentiment , while LR reached an accuracy of 92.3% with a more balanced classification. It is concluded that Logistic Regression is superior and more suitable for complex e-commerce review datasets, offering practical guidance for effective model selection
Co-Authors Yunus Widjaja