Sentiment Analysis of Cryptocurrency Exchange Application on Twitter Using Naïve Bayes Classifier Method - Indarso, Andhika Octa; Irmanda, Helena Nurramdhani; Astriatma, Ria (Telematika, 2023)
Purpose: The growth and development of the digital currency industry also presents a variety of applications for conducting transactions using these currencies, including utilizing cryptocurrency exchanges to make investments. InI ndonesia, there are two applications that fall into the category of the largest cryptocurrency exchange and are recognized by Bappebti (Commodity Futures Trading Regulatory Agency), namely TokoCrypto and Indodax. Both applications are analyzed based on the sentiments of their users on Twitter.Design/methodology/approach: In this study the data collected is data originating from social media Twitter and has the keywords "indodax" or "#indodax" and "tokocrypto" or "#tokocrypto". The data used is between January 2021 – January 2022. The data collected from Twitter is processed using the Naïve Bayes Classifier algorithm.Findings/result: From the results of the analysis, it was found that the Indodax application has a higher positive sentiment percentage value of 9% compared to TokoCrypto.Originality/value/state of the art: The use of the Naïve Bayes algorithm in this study supports sentiment analysis of cryptocurrency exchange application users to consider which application has better positive sentiment for investing in digital currency or cryptocurrency.