Pemodelan Profil Siswa SMP Berdasarkan Mathematics Self-Regulated Learning Menggunakan Metode K-Means Clustering - Munaji, Munaji (Imajiner: Jurnal Matematika dan Pendidikan Matematika, 2026)
Mathematics achievement at the junior high school level remains a significant challenge, with non-cognitive factors such as self-regulated learning (SRL) playing a critical role alongside cognitive ability. This study aims to develop a mathematical model for classifying Mathematics SRL profiles of junior high school students in Cirebon City using K-Means Clustering. A descriptive-exploratory quantitative design was employed with 68 students selected through stratified random sampling. Data were collected using a validated Mathematics SRL questionnaire (α = 0.823) encompassing four dimensions: Goal Setting, Self-Monitoring, Self-Efficacy, and Metacognition Motivation. Prior to clustering, data were standardized using Z-score normalization and analyzed through Principal Component Analysis (PCA). The optimal number of clusters (K = 3) was determined via the Elbow Method and Silhouette Index (SI = 0.286). Results identified three distinct student profiles: High (32.4%), Moderate (45.6%), and Low (22.1%), with statistically significant differences across all SRL dimensions (p 0.001). Self-Efficacy emerged as the most discriminating dimension (F = 70.349). The resulting classification model, C*(xᵢ) = , serves as a practical diagnostic tool for identifying student SRL profiles, enabling educators to design targeted, evidence-based pedagogical interventions.