<![CDATA[Advances in technology and information have a major influence on human life. The use of this technology has been widely used by humans, especially the use of internet technology. The internet that can be used at an affordable price and easily available supporting hardware has brought humans into a more modern era. In this study, sentiment analysis was carried out on the use of the Motion Banking application using the Support Vector Machine (SVM) algorithm and the Decision Tree algorithm. This study uses the Knowledge Discovery in Database (KDD) method. The purpose of this study is to classify review data from users of the Motion Banking application into positive and negative sentiments by studying user opinions about the Motion Banking application through the reviews provided, and to determine the performance of the classifier method used. In this study, data was obtained by collecting data from user reviews of the Motion Banking application on the Google Play Store using scraping techniques and managed to get 7000 review data. The best results were obtained in scenario 3 (70:30) using the Support Vector Machine algorithm with the Linear kernel which produced 93.7% accuracy, 93.6% precision, 91% recall, and 92.3% f1 score, while for The Decision Tree has an accuracy of 83%, a precision of 80.7%, a recall of 77%, and an f1 score of 79.1%.]]>
Copyrights © 2024
