Analisis Sentimen E-Wallet Menggunakan Support Vector Machine Berbasis Particle Swarm Optimization

E-Wallet applications in Indonesia have started to be demand since the Covid-19 pandemic. The object being analyzed is an e-wallet application that widely used and can downloaded on Google Playstore. are Dana, Ovo, PayPal Link Aja Doku. advantages of these five Dana user friendly or easy use, while using Ovo superior terms benefits, Doku security, tends perceived by consumers a neutral condition between security convenience because it e-wallet. It still considered new Indonesia, has become successful online payment system C2C field. focus this research compare comments users applications. method study Support Vector Machine (SVM) algorithm. To produce high accuracy optimized Particle Swarm Optimization (PSO) This was taken based previous studies which stated SVM-PSO highest percentage compared other algorithms. data thousand (1000) per application. So, total amount (5000) data. results show most positive comments, namely 579 421 negative lowest position occupied only negatuve comments. In process sentiment analysis, algorithm also obtained, 91.10% means very suitable combined get