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All Journal Jurnal Teknologi Informasi Mura Journal of Computing Theories and Applications
Helmi Roichatul Jannah
Universitas Jenderal Soedirman
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Prescriptive Learning Analytics for Student Dropout: Integrating Temporal Velocity and Counterfactual Explanations in Longitudinal Data Nurul Hidayat; Lasmedi Afuan; Helmi Roichatul Jannah
Journal of Computing Theories and Applications Vol. 3 No. 4 (2026): JCTA 3(4) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.15920

Abstract

Student dropout in higher education remains a persistent socioeconomic challenge, yet many predictive models reported in the literature are methodologically compromised by randomized cross-validation schemes that introduce temporal data leakage and artificially inflate predictive performance. This study proposes a longitudinal prescriptive learning analytics framework integrating three complementary methodological components: a Leave-One-Cohort-Out (LOCO) temporal validation protocol, a hybrid SMOTE-ENN class balancing strategy, and temporal velocity feature engineering derived from Learning Management System (LMS) behavioral trajectories. The framework was evaluated on a longitudinal dataset comprising 464,739 enrollment records and 77 features. Five predictive algorithms—XGBoost, LightGBM, CatBoost, Random Forest, and Logistic Regression—were comparatively assessed on a strictly isolated blind holdout cohort (2022), with CatBoost emerging as the champion estimator, achieving a PR-AUC of 0.8859, a Macro F1-Score of 0.9143, and the lowest Brier Score (0.0221), thereby demonstrating superior calibration and discriminative capability under severe class imbalance (93:7 ratio). Comprehensive ablation analysis revealed that temporal velocity features function not merely as additive predictors, but as a structural prerequisite enabling Synthetic Minority Oversampling Technique with Edited Nearest Neighbors (SMOTE-ENN) to generate high-quality synthetic boundary instances; removing these features reduced minority-class precision from 0.8302 to 0.6721. To operationalize predictive outputs into actionable intervention pathways, Diverse Counterfactual Explanations (DiCE) were implemented under a three-tier causal constraint architecture on 96 borderline high-risk students, generating 384 feasible intervention scenarios exclusively targeting forward-looking behavioral velocity metrics without constraint violations. Collectively, these findings advance the paradigm of prescriptive learning analytics by providing educational institutions with interpretable risk diagnostics and operationally feasible intervention guidance grounded in empirically validated behavioral and temporal dynamics.
A SYSTEMATIC REVIEW OF ERP ADOPTION IN SMALL AND MEDIUM ENTERPRISES: CHALLENGES AND OPPORTUNITIES IN DEVELOPING COUNTRIES Helmi Roichatul Jannah; Puteri Awaliatush Shofro; Novi Prisma Yunita
Jurnal Teknologi Informasi Mura (JTI) Vol. 17 No. 2 (2025): Jurnal Teknologi Informasi Mura DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v17i2.2889

Abstract

Enterprise Resource Planning (ERP) systems have become a critical enabler for organizational integration, efficiency, and digital transformation. However, the adoption of ERP systems among Small and Medium Enterprises (SMEs) in developing countries remains challenging and uneven. This study presents a systematic literature review of 71 peer-reviewed articles to examine the key challenges and opportunities associated with ERP adoption in SMEs within developing country contexts. Following the TOE (Technology Organization Environment) Framework, articles were screened, and analyzed from major academic databases. The synthesis reveals that technological factors (system complexity, compatibility, and data security), organizational factors (top management support, user competence, and resource constraints), and environmental factors (vendor support, regulatory pressure, and competitive intensity) are the dominant determinants influencing ERP adoption. Despite persistent challenges such as high implementation costs, resistance to change, and limited technical expertise, emerging opportunities-particularly cloud-based ERP, modular implementation strategies, and scalable subscription models-offer promising pathways for SMEs. This review contributes by consolidating fragmented empirical findings and identifying research gaps related to sustainability, post-adoption performance, and longitudinal impacts of ERP adoption in developing economies.
Co-Authors Hidayat, Nurul Lasmedi Afuan Novi Prisma Yunita Puteri Awaliatush Shofro