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All Journal Journal of Information Systems and Informatics Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Mimbar Kampus Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI)
Nurfebia, Karina
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Public Health Social Sciences Other

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Journal : Journal of Information Systems and Informatics

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Sentiment Analysis of Skincare Products Using the Naive Bayes Method Nurfebia, Karina; Sriani, Sriani
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.817

Abstract

The number of reviews about skincare products can be used as an evaluation of product quality and satisfaction from consumers who have used it as well as considerations for other consumers to try the product. With the number of reviews, it is important to classify reviews into positive, negative, and neutral classes so that the level of product quality from each classification class can be known. The number of reviews causes the review classification process to be unable to be carried out automatically, so sentiment analysis is carried out. To determine the classification of positive sentiment, negative sentiment, and neutral sentiment on the skincare product, the Naive Bayes algorithm method is used. Naive Bayes was chosen because it is easy to implement and has a probability value to classify data. To determine the percentage of results from the specified classification, the Confusion Matrix will be used. The results of the classification process using the Naive Bayes method produce data into 3 types, namely 65 positive classes, 87 neutral classes, and 24 negative classes with an accuracy value of 73%, precision 77%, recall 61%, and f1-score 63%.
Co-Authors Anggraini Srg, Dini Dimas Pratama, Dimas Jumiati, Ety Jumiaty, Ety Mughiroh, Hafizul Ramadhani, Nuzul Aini Sarif, Muhammad Irfan Sinulingga, Nurbeti Srg, Dini Anggraini Sulistia, Febri Yalda