IMPLEMENTASI ALGORITMA FUZZY C-MEANS DALAM CLUSTERING TINGKAT KEPUASAN MAHASISWA TERHADAP FASILITAS PENDIDIKAN - Abdul Aziz Ardana; Bambang Irwansyah (Smart Education, 2026)
The assessment of student satisfaction regarding educational facilities at the Faculty of Engineering, Universitas Asahan, has been subjective and limited to manual recapitulation. This study aims to implement a web-based Fuzzy C-Means (FCM) algorithm (using PHP and MySQL) to group student satisfaction levels more objectively. This study uses primary data obtained from questionnaires given to 200 respondents. Based on the computational testing results, the FCM algorithm successfully reached convergence and grouped the data into three clusters. From a total of 200 data, 89 respondents were in the Dissatisfied cluster (C1), 64 respondents in the Moderately Satisfied cluster (C2), and 47 respondents in the Satisfied cluster (C3). This system is also capable of grouping qualitative data in the form of student suggestions according to their clusters. This implementation is proven effective in generating accurate information as a comprehensive evaluation report for faculty leaders to prioritize eduacational facility improvements.