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All Journal Journal of Systems Engineering and Management
M Wahyudi Hasibuan
Trisakti University
Control & Systems Engineering Engineering Industrial & Manufacturing Engineering

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Customer Reviews Based Sentiment Analysis Utilizing the Naïve Bayes Algorithms and Random Forest Classifier for Aren Latte Coffee from a Startup Company M Wahyudi Hasibuan
Journal of Systems Engineering and Management Vol 5, No 1 (2026)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/joseam.v5i1.39497

Abstract

Everyone enjoys sipping coffee. Customers are currently enjoying palm sugar lattes. Startups like Kenangan Group, PT Kopi Bintang Indonesia, and PT Luna Bog Narayan are among the businesses vying to produce palm sugar lattes. Examining consumer sentiment—more especially, their reactions and responses—about palm sugar lattes is the aim of this study. A random forest coefficient matrix with superior results of 67%, 70.49%, and 65.10% was obtained using data gathered from X and processed using Python with the random forest and Naive Bayes algorithms, whereas Naive Bayes produced values of 56.90%, 66.39%, and 65.14%. Additionally, compared to PT Luna Boga Narayan and Kenangan Group, PT Kopi Bintang Indonesia has a greater positive sentiment score of 47%, whilst PT Luna Boga Narayan has a higher negative sentiment rate of 61%. A random forest coefficient matrix with superior results of 67%, 70.49%, and 65.10% was obtained using data gathered from X and processed using Python with the random forest and Naive Bayes algorithms, whereas Naive Bayes produced values of 56.90%, 66.39%, and 65.14%. Additionally, PT Luna Boga Narayan has a greater negative sentiment rate of 61% compared to Kenangan Group and PT Kopi Bintang Indonesia, whereas PT Kopi Bintang Indonesia has a higher positive sentiment rate of 47%..
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