Analisis Sentimen Menggunakan Metode Naive Bayes dan Support Vector Machine pada Ulasan Aplikasi Joox Music

Abstract

In this digital era, user reviews of mobile applications play an important role in shaping people's perception of a product or service. This study presents an analysis of opinion reviews of Joox music application users using the Bayesian Naïve classification method. The Naive Bayes method is used to classify user ratings into positive, negative, or neutral opinion categories. The dataset contains a large number of Joox music user reviews, added manually and used as examples in this study. The results of sentiment analysis show that the Bayesian Naive method can identify and classify the sentiment of Joox music user reviews very accurately. These findings provide developers with valuable information to understand user opinions and respond more effectively to customer feedback. The study also helps to understand the effectiveness of the Bayesian Naive classification method in handling large and complex user review data.