Hybrid Approach of LDA, ROS-NCL, and CNN for Topic Mining in Fintech User Reviews

The development of digital payment technology, such as Gopay, has provided convenience for the Indonesian public. To understand user satisfaction and identify key issues, this study analyzes Gopay user reviews using a hybrid approach. The main issues addressed are the imbalance in review data and the lack of studies integrating Latent Dirichlet Allocation (LDA) and Convolutional Neural Network (CNN) models for topic analysis. This research encompasses three main stages: topic identification using LDA, data balancing with Random Over Sampling and Neighborhood Cleaning Rule (ROS-NCL), and topic classification using CNN. The model is designed to accurately identify and classify key topics. Furthermore, this method is compared with other approaches to assess its advantages. The research findings show that this hybrid approach is effective in addressing data imbalance, achieving a topic classification accuracy of 96%. These findings provide valuable insights for service providers to improve the quality of Gopay services based on topic analysis derived from user feedback.