Mapping Multidimensional Disparities of Elementary School Carrying Capacity in Indonesia: A PCA-Based Provincial Analysis
DOI:
https://doi.org/10.51700/alifbata.v6i2.2050Keywords:
educational evaluation, school feasibility, principal component analysis, regional disparity, elementary educationAbstract
Educational feasibility at the elementary level in Indonesia remains uneven across regions despite sustained policy efforts to improve access and quality. This study aims to evaluate and map the feasibility of elementary education across all 38 Indonesian provinces by integrating indicators of human resources, physical infrastructure, and operational efficiency into a single evaluative framework. Employing a quantitative descriptive exploratory design using province level education statistics, five ratio based indicators, qualified teacher ratio, proper classroom ratio, teacher workload, class density, and dropout rate, were constructed. Data were analyzed using Principal Component Analysis (PCA) to reduce dimensionality and identify latent factors underlying inter-provincial disparities. Instrument suitability for factor analysis was validated using the Kaiser-Meyer-Olkin measure and Bartlett’s test of sphericity. The analysis retained two principal components, collectively explaining 83.1 percent of the total variance. The first component represents operational efficiency and human resource quality, characterized by high teacher workload, dense class groupings, and an inverse relationship with teacher qualification. The second component reflects physical carrying capacity and student retention, dominated by classroom conditions and dropout rates. Interpretation of component scores through quadrant mapping reveals regional polarization: densely populated provinces show adequate physical facilities but severe capacity overload, while eastern regions face combined constraints in both infrastructure quality and human resource capacity. This study offers a novel PCA-based evaluative model, indicating that educational feasibility is multidimensional and cannot be inferred from infrastructure alone, highlighting the need for cluster-based policy interventions aligned with specific regional capacity profiles.
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