Analisis Sentimen Ulasan Pengguna Pada Aplikasi BRImo BRI Menggunakan Metode Klasifikasi Algoritma Naive Bayes

 (*)Muhammad Umair Mail (Universitas Teknokrat Indonesia, Lampung, Indonesia)
 Erliyan Redy Susanto (Universitas Teknokrat Indonesia, Lampung, Indonesia)

(*) Corresponding Author

Submitted: January 20, 2024; Published: April 30, 2024

Abstract

Sentiment analysis is the process of collecting, measuring, understanding and interpreting opinions or sentiments expressed in text to understand or evaluate the opinions contained in a topic. BRImo BRI application analysis research aims to analyze the sentiment of user reviews of the BRImo BRI application via the Google Play Store platform using the Naive Bayes Algorithm Classification method. This algorithm is used to identify Positive, Negative and Neutral sentiment patterns contained in user reviews of the BRImo BRI application via the Google Play Store platform. The data used in this research was 199 data. The sentiment results obtained from these data were Positive sentiment as many as 47, Negative as many as 125 and Neutral as many as 27. After analyzing the data using the Naive Bayes algorithm classification, the data results obtained were accuracy results of 65%, precision results of  67%, recall results of  92%. and f1_score results 77%. This research aims to analyze the sentiment of user reviews of the BRImo BRI application regarding payment features via the Google Play Store platform using the Naive Bayes Algorithm Classification method. The Naive Bayes algorithm is used to analyze Positive, Negative and Neutral sentiments that appear in user reviews of the BRImo BRI Application regarding payment features. Analysis of user sentiment towards the application is very important for service providers to understand user perceptions and needs in the BRImo BRI application.

Keywords


BRImo BRI Application; Google Play Store; Naive Bayes Algorithm Classification; Sentiment Analysis

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