Analisis Sentimen Ulasan Pengguna QRIS pada Aplikasi GoPay: Studi Komparatif Algoritma Support Vector Machine dan Decision Tree Berbasis TF–IDF - Erlinda Sistia Aritonang; Yuwan Jumaryadi (Forum Kerjasama Pendidikan Tinggi (FKPT), 2026)
This study aims to analyze user sentiment towards the QRIS feature in the GoPay application based on reviews on the Google Play Store and to build a sentiment classification model using a machine learning approach. A total of 20,746 reviews were collected and filtered using QRIS-related keywords, resulting in 4,347 relevant reviews. The data were manually labeled and preprocessed, then extracted using the TF–IDF method. The analysis results show a sentiment distribution consisting of 49.49% positive, 35.34% negative, and 15.18% neutral. The classification process was carried out using the Support Vector Machine (SVM) and Decision Tree algorithms. The evaluation results showed that Decision Tree achieved 79% accuracy with precision, recall, and F1-score values ​​of 79% each, while SVM produced 78% accuracy with precision of 79%, recall of 78%, and F1-score of 78%. The difference in performance between the two models was relatively small, so both had equal capabilities in sentiment classification, although Decision Tree showed slightly better metric consistency.