Analisis Sentimen Aplikasi Dana Menggunakan Naïve Bayes Classifier dan Support Vector Machine - Gabriel Genaro Warow; Henry Pandia (STMIK Banjarbaru, 2024)
AbstractThe presence of financial technology (fintech) has introduced a new payment system that is practical, easily accessible, and efficient, such as the Dana application. However, to understand user acceptance of this application, sentiment analysis was required. This study aimed to analyze user opinions on the Dana application through their reviews and evaluate the performance of Naïve Bayes Classifier and Support Vector Machine algorithms in classifying sentiments. User review data was obtained through the Google Play Scraper API. From the sentiment analysis, it was concluded that the majority of users (84.7%) had a negative view of the Dana application, while only 8.8% provided positive sentiment, and 6.5% were neutral. Performance evaluation indicated that both Naïve Bayes Classifier and Support Vector Machine functioned effectively in classifying review data.Keywords: Naïve Bayes Classifier; Support Vector Machine; Dana Application AbstrakKehadiran teknologi finansial (fintech) telah menghadirkan sistem pembayaran baru yang praktis, mudah diakses, dan efisien seperti aplikasi Dana. Namun, untuk memahami penerimaan pengguna terhadap aplikasi tersebut, analisis sentimen diperlukan. Penelitian ini bertujuan untuk menganalisis opini pengguna terhadap aplikasi Dana melalui ulasan mereka, serta mengevaluasi kinerja algoritma Naïve Bayes Classifier dan Support Vector Machine dalam mengklasifikasikan sentimen. Data ulasan pengguna diperoleh melalui API Google Play Scraper. Dari analisis sentimen, disimpulkan bahwa sebagian besar pengguna (84,7%) memiliki pandangan negatif terhadap aplikasi Dana, sedangkan hanya 8,8% memberikan sentimen positif, dan 6,5% bersifat netral. Evaluasi kinerja menunjukkan bahwa baik Naïve Bayes Classifier maupun Support Vector Machine berfungsi efektif dalam mengklasifikasikan data ulasan.