Klasterisasi Sentimen pada Ulasan Aplikasi LINE Bank menggunakan Algoritma K-Means Clustering
Keywords:
google play store, k-means clustering, LINE bank, sentiment analysis, TF-IDFAbstract
Financial digital banking applications have become an integral part of daily life. One of the digital banking applications widely used by the public is LINE Bank. This study aims to analyze user sentiment based on reviews of the LINE Bank application available on the Google Play Store platform. The data were collected using a web scraping technique from user reviews on Google Play Store. The analysis method employed in this study is K-Means Clustering with Term Frequency–Inverse Document Frequency (TF-IDF) as the weighting method. The clustering process is expected to group user reviews based on sentiment tendencies and identify dominant issues experienced by users. The results of this study can be used as evaluation material for application developers to improve service quality and enhance user satisfaction.
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