Penerapan Algoritma K-Means Clustering untuk Pengelompokan Tingkat Kepuasan Pengguna Aplikasi Smart Home CCTV Berdasarkan Usia Pengguna. - Fernando Otniel Haliwela; Nabil Ihsan Kurnia Sandy; Saviola Apu; Guido Setia Murniawan Zebua; Fachri Amsury; Riza Fahlap Fahlapi (JURNAL TEKNOLOGI INFORMASI, 2026)
This study aims to classify the satisfaction levels of Smart Home CCTV (DMSS) application users based on their age using the K-Means Clustering algorithm. The data were collected through a questionnaire consisting of 12 indicators covering ease of use, access speed, application stability, interface clarity, and data security. The analysis process involved data cleaning, normalization, determining the optimal number of clusters using the Elbow Method, and applying the K-Means algorithm until convergence was achieved. The results produced three main clusters representing variations in user satisfaction, ranging from highly satisfied, moderately satisfied, to average satisfaction groups. Overall, the DMSS application is perceived to provide a positive user experience, although certain aspects such as system performance and application stability still require improvement. These findings are expected to assist developers in enhancing service quality and improving user experience on an ongoing basis.