Sentiment Analysis in E-Commerce: Beauty Product Reviews - Tumanggor, Gavrila Louise; Samosir, Feliks Victor Parningotan (Faculty of Engineering and Informatics, Universitas Multimedia Nusantara, 2024)
The increasing popularity of online shopping platforms is fueling the need for automated sentiment analysis for product reviews. This research aims to build an automatic sentiment analysis model in Indonesian for e-commerce product reviews. This model is expected to help consumers make purchasing decisions more quickly. We utilize the IndoBERT model, which has shown to be quite effective for general sentiment analysis, achieving an evaluation accuracy of 66.2% despite a high evaluation loss of 0.8006. The approach used combines Natural Language Processing (NLP) and Machine Learning (ML) techniques. It is hoped that this research will be useful for consumers, shop owners, and researchers in efficiently understanding the sentiment of e-commerce product reviews.