X-Means Clustering for UX Evaluation of the Candy CBT Application Using the SUS Instrument

Abstract

The Candy CBT application at SMKS Pancabudi Medan has been operating for three years without adequate usability reviews, posing a high risk of serious problems in user experience (UX), especially in terms of system responsiveness. Therefore, this study aims to analyze the level of system usability and group users based on three aspects (GUI, Navigation, and Responsiveness) using X-Means Clustering to develop recommendations for improvement. The method used is a data mining-based evaluative study involving 400 respondents of a modified System Usability Scale (SUS) questionnaire, with data processed through reverse scoring and Z-Score Normalization before clustering. The results show that the GUI (4.53) and Navigation (4.51) aspects are rated very good. Still, responsiveness is very low (1.48), becoming a major weakness consistent across all clusters. The X-Means Clustering model automatically determined two optimal clusters, with the most dominant cluster specifically showing extreme dissatisfaction with responsiveness (score 1.08). This study contributes a more granular usability evaluation approach by integrating aspect-based SUS features with X-Means Clustering, enabling more precise identification of critical UX weaknesses and supporting data-driven prioritization of usability improvements in CBT systems. Therefore, the application's usability needs to be significantly improved, and recommendations should focus on enhancing non-functional requirements, particularly system performance and stability, to ensure better multi-device responsiveness, with the cluster showing the highest dissatisfaction as the top priority.