COMPARATIVE ANALYSIS OF SHOPEE AND TIKTOK SHOP USER SENTIMENT USING NAÏVE BAYES ALGORITHM - Lestari, Putri Dwi; Hidayah, Agung Kharisma; Saputera, Surya Ade; Erwadi, Yetman; Alam, RG Guntur (Jurnal TAM (Technology Acceptance Model), 2025)
The rapid growth of e-commerce has influenced changes in people's online shopping behaviour. Shopee and TikTok Shop are two popular e-commerce platforms in Indonesia, each offering unique features and shopping experiences. This research aims to analyse and compare user sentiment towards the two platforms by applying Naïve Bayes algorithm. User review data was obtained from Google Play Store through web scraping technique, then processed using Knowledge Discovery in Database (KDD) approach, which includes data collection, preprocessing, transformation, modelling, and evaluation stages. Naïve Bayes algorithm was used to classify the sentiment of the reviews into positive or negative categories. The results show that the majority of reviews for both platforms are positive, with Shopee having a higher proportion of positive sentiment than TikTok Shop. The model used shows good accuracy in classifying sentiment, although there is still a tendency to bias towards positive sentiment. The findings are expected to provide insights for e-commerce platform managers in improving service quality and better understanding user preferences.