Perbandingan Naïve Bayes dan Logistic Regression untuk Analisis Sentimen Ulasan Produk Skincare di Tokopedia - Indra Dikusuma; Yunus Widjaja (Pusat Riset dan Inovasi Nasional, 2025)
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