Nur Izzaty, Adelia Shinta, Riski Arifin, Sri Rahmawati
The increasing development of technology nowadays has led to the transformation of customers behaviour in purchasing products, from offline to online through marketplace. One of the most popular marketplaces in Indonesia is Shopee with the best seller skincare product is organic face mask. This study aims to analyse the sentiment of customer reviews using natural language processing (NLP) and term frequency-inversed document frequency (TF-IDF). The result revealed that from 882 reviews extracted, 89.7% was classified as positive reviews (rating 4 and 5) and the rest as much as 10.3% was the negative ones (rating 1 and 2). The sentiments were visualised using word cloud. Among the positive reviews were ‘very good’, ‘quickly absorbed’, and ‘convenient’. Meanwhile, among the negative reviews were ‘disappointed’, ‘delivery’, and ‘acne’. In summary, the performance metrics used for the evaluation of the classification model showed that the model accuracy reached 95%. Copyright © 2025 Inderscience Enterprises Ltd.
Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Indonesia
Research at a Glance
Register to unlock
Topics & SDG Alignment
Register to unlock
Collaboration
Register to unlock
Author Profile (Selected)
Register to unlock
References Overview
Register to unlock
Journal & Source
Register to unlock
Metadata & Integrity
Register to unlock