Sentiment Analysis of Review Sestyc Using Support Vector Machine, Naive Bayes, and Logistic Regression Algorithm

Abstract

The growth of internet users in Indonesia experiences a very high increase every year, with the increase in internet users in Indonesia also resulting in many people using social media. Sestyc is a social media application created by a group of millennial children in Indonesia. This study was conducted to analyze the sentiment of users of Sestyc using text data in the form of a review obtained from the Google Play Store. The purpose of this research is to analyze sentiment towards the sestyc application and find the best algorithm for classifying sentiment. The algorithm used in analyzing sentiment in this study consists of Support Vector Machine, Logistic regression, and Naive Bayes. The results of sentiment class labeling on the sestyc review data obtained 8000 reviews with a total of 4719 positive reviews and 3281 negative reviews. The results of this study indicate that the Support Vector Machine algorithm has the highest accuracy value compared to other algorithms, where the Support Vector Machine gets an accuracy value. by 87.81%.