ANALISIS PROFILING KINERJA DOSEN BERBASIS ALGORITMA CLUSTERING: STUDI KASUS DATA EVALUASI MAHASISWA (EDOM) - Heri Subangkit; Taqwa Hariguna; Dhanar Intan Surya Saputra (LPPM Universitas Abdurrab, 2026)
Lecturer quality is a key factor determining the success of a higher education institution. Although EDOM assessment is crucial for performance, large data processing often does not provide sufficient strategic information. This study utilizes a no-learning method to profile lecturer performance. K-Means and Fuzzy C-Means (FCM) are two clustering algorithms that are compared with four competency variables. These variables are pedagogical, professional, social, and personality. The results show that there are three ideal clusters (k = 3) which are categorized as