Perbandingan Kinerja Support Vector Machine Dan Random Forest Untuk Klasifikasi Sentimen Pengguna Aplikasi Gojek Dengan Optimasi Smote - Rihastuti, Siti; Rosyidi, Afnan (Program Studi Teknik Informatika Universitas Multi Data Palembang, 2025)
This study compares the performance of Support Vector Machine (SVM) and Random Forest in classifying Gojek user sentiment using 2,000 Indonesian-language reviews (1,351 positive, 566 negative, 83 neutral). After data preprocessing and TF-IDF feature extraction, SMOTE was applied to balance the training data in each fold. Using Stratified K-Fold Cross-Validation, results showed that Random Forest achieved higher and more consistent accuracy (84.1%) than SVM (76.1%). The Paired t-test and McNemar’s Test (p-value < 0.05) confirmed that the Random Forest’s superiority was statistically significant. Overall, both models were effective, but Random Forest performed better for Gojek sentiment classification, supporting user satisfaction monitoring and complaint detection.