The Sentiment Analysis of Fintech Users Using Support Vector Machine and Particle Swarm Optimization Method

This research was conducted to analyze the sentiment of Fintech users in Tegal City, especially the Ovo application since it currently has a very massive market and promotion. Users choosing the Fintech application generally consider convenience, security, transaction suitability, convenience, and cashback. The problem is that the user's trust in Fintech is still in doubt. Currently the application provides reviews to share their experiences. With the number of reviews displayed, it needs analysis that can classify the review into positive or negative classes. This research is using experimental method. Data is taken from Google Play in the OVO Application. The method used is the method of Support Vector Machine (SVM) and Particle Swarm Optimization (PSO). Data processing is using the Application RapidMiner Studio 7.6.003. The result is that the Ovo application gets the best value with an accuracy of 82.33%. So that it can be concluded that the results of the review might convince users of other positive customer experiences while negative experiences can be used as a contribution to the thinking of the next product development to be better so they can compete.