Sentiment Modeling of Instagram Users Towards Traditional and Modern Body Scrubs Using the Naive Bayes Algorithm

Mardiana Mardiana, Kusrini Kusrini
DOI: https://doi.org/10.33650/jeecom.v7i1.10175



Abstract

This study conducts sentiment analysis on Instagram comments related to traditional and modern body scrub products using the Naive Bayes algorithm. The aim of the research is to identify and compare consumer sentiments—positive, negative, or neutral—toward these two categories of skincare products. The results indicate that neutral sentiment dominates, followed by negative and positive sentiments. The Naive Bayes algorithm demonstrated strong performance, particularly in detecting negative and neutral sentiments, but exhibited a lower recall rate for positive sentiments. The findings reveal that consumers value traditional body scrubs for their natural ingredients and cultural significance, while modern body scrubs are appreciated for their innovation. These insights offer actionable recommendations for skincare brands, highlighting the need for tailored marketing strategies and deeper consumer engagement.


Keywords

Sentiment Analysis; Naïve Bayes; Body Scrub; Consument Perception; Instagram

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10.33650/jeecom.v7i1.10175


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Copyright (c) 2025 Mardiana Mardiana, Kusrini Kusrini

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Creative Commons License
 
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Journal of Electrical Engineering and Computer (JEECOM)
Published by LP3M Nurul Jadid University, Indonesia, Probolinggo, East Java, Indonesia.