PENERAPAN NATURAL LANGUAGE PROCESSING UNTUK ANALISIS SENTIMEN ULASAN APLIKASI ALLO BANK MENGGUNAKAN ALGORITMA SVM - Singgih Adhi Prasetyo; Diana Yusuf; Muhajir Syamsu (ITB Ahmad Dahlan Jakarta, 2026)
The rapid growth of digital banking applications in Indonesia requires companies to pay close attention to user perceptions and satisfaction. This research focuses on analyzing the sentiment of user reviews of the Allo Bank application obtained from the Google Play Store, applying the Support Vector Machine (SVM) algorithm combined with a Natural Language Processing (NLP) approach. A total of 5,100 reviews in the Indonesian language were collected using web scraping methods. The analysis involved several stages, including text preprocessing, term weighting with TF-IDF, sentiment classification into three categories (positive, negative, and neutral), and performance evaluation of the model. The findings reveal that most user reviews express positive sentiment, with frequently appearing words such as