SENTIMENT ANALYSIS DESIGN OF PRODUCT REVIEWS IN THE MARKETPLACE USING NAIVE BAYES CLASSIFIER METHOD; A CASE STUDY IN TOKOPEDIA

Widnyani, N.M; Aristayudha   A.A.N.B; Sugianta, I.K.A

Authors

Widnyani, N.M Program Studi Bisnis Digital, Fakultas Bisnis Sosial Teknologi dan Humaniora Universitas Bali Internasional
Aristayudha A.A.N.B Program Studi Bisnis Digital, Fakultas Bisnis Sosial Teknologi dan Humaniora Universitas Bali Internasional
Sugianta, I.K.A Program Studi Bisnis Digital, Fakultas Bisnis Sosial Teknologi dan Humaniora Universitas Bali Internasional

Keywords:

Naive Bayes Classifier, sentiment analysis,

Abstract

This study aimed at analyzing sentiment of product purchase reviews on the Tokopedia marketplace using the Naive Bayes Classifier (NBC) algorithm. It was a qualitative study which was done in Bali International University. Two types of data contained in this study namely, primary data and secondary data. Product review became the primary data and information from reference books and journals became the secondary data. It was a qualitative study which focused on sentiment analysis of product reviews in Tokopedia by using Naïve Bayes Classifier (NBC) method. The NBC method is commonly used as a probabilistic learning method to find the highest probability value in classifying the data and getting the appropriate category. There were some staged to be followed such as problem analysis and data collection, library research of sentiment analysis by using NBC method, sentiment analysis process by using NBC method, NBC method testing, and conclusion. The data were collected from research study, observation, and questionnaires. From the three data collection models, data analysis was carried out with the following models such as data reduction, data display, and conclusion. The result of this study showed that the result of respondents answered, or sentiment matched to the sentiment classification system designed

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