A Analysis of Public Sentiment towards Beverage Franchise Reviews Using the Naïve Bayes Algorithm

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Published: Sep 20, 2023
DOI: https://doi.org/10.54209/jurnalkomputer.v15i01.102
Keywords:
Franchising, Sentiment Analysis, Naïve Bayes.
Issue
Vol. 15 No. 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Section
Articles
Statistics Article
Article View : 38 Times

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maya khairani
Fakultas Sains dan Teknologi Universitas Islam Negeri Sumatera Utara Medan
Abdul Halim Hasugian
Universitas Islam Negeri Sumatera Utara Medan
Raissa Amanda Putri
Universitas Islam Negeri Sumatera Utara Medan

Abstract

A franchise is an individual or business that is licensed to use the intellectual property or business characteristics of the franchisor. Currently, the food and beverage business is very familiar because of its rapid development, one of which is boba drinks. In the food business, customer ratings and reviews are very important because they can provide suggestions and input to improve the quality of the products sold. This study analyzes drink reviews by differentiating positive and negative reviews in the text mining process using Naïve Bayes. Data was taken from Google reviews with a total of 132 data consisting of 81 positive reviews, 38 neutral and 13 negative. The accuracy of positive reviews is 70% and for all reviews it reaches 81%.

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How to Cite
khairani, maya, Hasugian, A. H., & Putri, R. A. (2023). A Analysis of Public Sentiment towards Beverage Franchise Reviews Using the Naïve Bayes Algorithm. Instal : Jurnal Komputer, 15(02), 89–98. https://doi.org/10.54209/jurnalkomputer.v15i01.102
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