Andi Quraisy
Muhammadiyah University of Makassar

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Pemetaan Pola Prokrastinasi Akademik Mahasiswa Dalam Pembelajaran Melalui Principal Component Analysis Andi Quraisy; Nursakia Nursakia
Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Vol. 9 No. 3 (2026): Volume 9 Nomor 3 Tahun 2026
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/proximal.v9i3.9642

Abstract

Academic procrastination is a complex behavior that can manifest in various forms, such as delaying the initiation and completion of assignments, working on tasks close to deadlines, engaging in last-minute studying, submitting assignments late, diverting study time to other activities, and experiencing difficulties in managing academic time. This study aimed to identify the principal component structure of students’ academic procrastination behavior based on 21 academic behavior items using Principal Component Analysis (PCA). The study employed an exploratory quantitative approach involving 55 respondents selected through convenience sampling. Data were collected using a five-point Likert-scale questionnaire and analyzed using the Kaiser-Meyer-Olkin (KMO) measure, Bartlett’s Test of Sphericity, Measure of Sampling Adequacy (MSA), communalities, eigenvalues, scree plot, and Varimax rotation. The analysis showed a KMO value of 0.850 and a significant Bartlett’s Test, χ²(210) = 771.259, p < 0.001, indicating that the data met the requirements for PCA. All items had MSA values ranging from 0.706 to 0.899, exceeding the minimum criterion of 0.50, indicating that all items were suitable for retention based on MSA. The extracted communalities ranged from 0.470 to 0.810, while the primary rotated component loadings ranged from 0.564 to 0.857. Based on the eigenvalue > 1 criterion, four principal components were obtained, cumulatively explaining 68.56% of the total variance. The four components were interpreted as academic delay behavior, last-minute learning patterns, difficulties in academic time management, and late assignment submission. The findings provide a more structured representation of academic procrastination patterns and may serve as a basis for developing student support strategies and managing students’ academic learning activities.