Perbandingan Naïve Bayes dan Logistic Regression untuk Analisis Sentimen Ulasan Produk Skincare di Tokopedia

Jurnal Informatika Dan Tekonologi Komputer
Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer

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