Title: Sentiment analysis on customer reviews in Indonesian marketplace using natural language processing (a case study of organic face mask)

Authors: Nur Izzaty; Adelia Shinta; Riski Arifin; Sri Rahmawati

Addresses: Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Indonesia ' Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Indonesia ' Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Indonesia ' Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Indonesia

Abstract: 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%.

Keywords: customer reviews; natural language processing; NLP; sentiment analysis; term frequency-inverse document frequency; TF-IDF; skincare; organic face mask.

DOI: 10.1504/IJDMMM.2025.148839

International Journal of Data Mining, Modelling and Management, 2025 Vol.17 No.3, pp.364 - 381

Received: 11 Mar 2024
Accepted: 18 Aug 2024
Published online: 29 Sep 2025 *

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