Sentiment Analysis Based on Review on Flip Application in Google Playstore
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Abstract
Money is one of the legal means of exchange for payment, both in the form of cash and electronic money which is allocated in the form of balances. Along with the development of technology, the use of electronic money is increasingly being used. Electronic money also makes it easier to send transfer-based money. However, transfer-based remittances incur an additional fee as an administration fee. In Google Play Store, there are several transfer applications without administration fees. Flip application is one of application which has a high review score and the highest number of downloads on transfer-based applications. Almost all users before using the application rely on comments as a consideration in using the application, because these comments provide the latest information from the point of view of users who have used the application. Comments that number in the hundreds of thousands certainly have difficulty analyzing each comment manually, so a sentiment analysis process is carried out. This study used Decision Tree, Naïve Bayes, and Backpropagation Neural Network methods for classifying sentiment. The Backpropagation Neural Network method has the best classification evaluation in terms of accuracy, recall, and F1-Score, with an average value of 87.85%, 97.49% and 91.39% respectively.
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