Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Rini Handayani , Maya
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sentiment Analysis customer Towards Cinema Services in Semarang Using Naive Bayes Classifier on Google Reviews Brian Maualan, Husni; Rini Handayani , Maya; Umam, Khotibul
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10974

Abstract

The development of the entertainment industry, especially in the field of cinema, encourages every service provider to continuously maintain the quality of their services. One method of assessing customer satisfaction is through sentiment testing. The main objective of this study is to examine customer sentiment towards cinema services in Semarang by applying the Naive Bayes Classifier method. The research data was taken from 600 customer reviews on Google Review, which were then divided into two groups: training data consisting of 480 reviews (80%) and testing data consisting of 120 reviews (20%). Before the classification process, the data underwent pre-processing stages involving data cleaning, case folding, tokenization, stopword removal, and stemming, followed by data labeling into two sentiment categories, namely positive and negative. This study took five cinemas as objects, namely CitraXXI, Cinépolis Java Mall, Paragon XXI, XXI Uptown Mall, and XXI DP Mall. The classification results show that the Naive Bayes algorithm is able to group sentiments quite well, with model accuracy ranging from 0.90 to 0.94. Of the five cinemas, Cinépolis Java Mall achieved the highest accuracy, which was 0.94.
Co-Authors Brian Maualan, Husni Khotibul Umam