<![CDATA[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 "voice of the customer" in the QFD method. By constructing a House of Quality (HoQ) matrix, the study established a priority ranking of technical responses. These responses include strategies to optimize tools, application features, and memory usage, reduce excessive animation and the use of live wallpapers, create an update mechanism, provide content localization features, continuously incorporate customer feedback into application improvements.]]>
