Improving the quality of mobile banking services using the integration of text mining, mobile banking service quality, and Quality Function Deployment - Bahauddin, Achmad; Ulfah, Maria; Boru Angin, Nurul Fadillah; Fachrur, Aditya Rahadian (Universitas Sultan Ageng Tirtayasa, 2024)
Customer service quality is a key performance indicator that directly impacts a company's image. This study identified potential issues with a mobile banking app (m-banking) based on its low rating on the Google Play Store compared to similar apps. The app's rating likely reflects user satisfaction with the m-banking service. To address these concerns and improve service quality based on user feedback (voice of customer), a study was conducted using three methods: text mining, mobile banking service quality analysis, and Quality Function Deployment (QFD). The text mining method analyzed sentiment from comments on the Google Play Store. It employed a Support Vector Machine (SVM) algorithm, achieving high accuracy (0.86), precision (0.86), recall (0.84), F1-score (0.85), and AUC (0.84). Negative sentiment analysis identified five dimensions encompassing 15 attributes of m-banking service quality. These attributes were then incorporated into a questionnaire distributed to 100 respondents. Six attributes with the lowest gap values were identified as priority attributes, representing the most critical customer concerns. These attributes were used as the