ANALISIS SENTIMEN PENGGUNA PADA APLIKASI BANK DIGITAL KROM DENGAN ALGORITMA SUPPORT VECTOR MACHINE
DOI:
https://doi.org/10.31949/infotech.v10i2.11801Abstract
The rapid development of financial technology has driven the widespread adoption of digital banking applications, including the KROM app, among the public. This study aims to analyze user sentiment toward the KROM Digital Bank application using the Support Vector Machine (SVM) algorithm. User review data was collected from Google Play, then processed through data preprocessing steps such as text cleaning, tokenization, and removing irrelevant words. The SVM algorithm is used to classify user sentiment into positive and negative categories. The results indicate that SVM performs well in classifying user sentiment, with an accuracy of 84,38%. This analysis is expected to provide insights for app developers to improve service quality based on user perceptions and experiences.
Keywords:
text mining, Sentiment Analysis, Digital Bank, support vector machineDownloads
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