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All Journal Zero : Jurnal Sains, Matematika, dan Terapan
Ika Nur Laily Fitriana
Statistics Study Program, Universitas Terbuka, South Tangerang, 15437, Indonesia
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics

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Ensemble Anomaly Detection and SHAP-Based Attribution for Mapping Educational Inequality across Indonesian Provinces Emeylia Safitri; I Gusti Ngurah Sentana Putra; Yeni Rahkmawati; Ika Nur Laily Fitriana; Nuramaliyah Nuramaliyah; Ria Faulina
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 2 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i2.31161

Abstract

Educational inequality across Indonesia’s 38 provinces remains a challenge to equitable development. This study identifies anomalous provincial educational profiles by comparing Isolation Forest, Local Outlier Factor, and One-Class SVM across 50 parameter configurations in five analytical categories. The framework integrates ensemble majority voting, SHAP-based attribution, and leave-one-out robustness testing. Under the Silhouette-based selection criterion, Isolation Forest with contamination 0.05 ranked highest in four categories, with Silhouette Scores of 0.47-0.60 and Stability Scores of 1.0. However, sensitivity analysis showed that this criterion tends to favor configurations detecting fewer anomalies, so IF (0.05) should not be considered unambiguously superior. Highland Papua was consistently identified as anomalous across all categories. SHAP highlighted socioeconomic indicators, particularly rural child-labor participation, as important contributors to anomaly scores. Given the single-year design, 38 observations, and high feature-to-sample ratio, findings should be interpreted as exploratory descriptive mapping rather than causal or broadly generalizable inference.
Co-Authors Emeylia Safitri I Gusti Ngurah Sentana Putra Nuramaliyah, Nuramaliyah Ria Faulina Yeni Rahkmawati