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All Journal Jurnal Teknologi Terpadu Journal of Data Insights
Sholihul Ibad
Institut Teknologi dan Bisnis Tuban
Computer Science & IT Engineering Mathematics

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Development of a Decision Support System for Regional Competitiveness Policy Recommendations Based on Explainable Artificial Intelligence (XAI): Pengembangan Sistem Pendukung Keputusan untuk Rekomendasi Kebijakan Daya Saing Regional Berdasarkan Explainable Artificial Intelligence (XAI) Sintha Istikomah; Dwi Purnomo Putro; Sholihul Ibad; Aditya Hermawan
Journal of Data Insights Vol 4 No 1 (2026): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v4i1.1141

Abstract

Enhancing regional competitiveness is a critical factor in driving economic growth, investment, and community welfare. However, the utilization of Regional Competitiveness Index (Indeks Daya Saing Daerah/IDSD) data in Indonesia has largely been limited to ranking purposes, thus failing to provide specific, data-driven policy recommendations. This study aims to develop a Decision Support System (DSS) for regional competitiveness policy recommendations by combining machine learning and Explainable Artificial Intelligence (XAI) within a Design Science Research (DSR) framework. The dataset originates from provincial IDSD data spanning 2022–2025, encompassing 12 assessment pillars as predictor variables. Three regression algorithms were examined: Linear Regression, Random Forest, and XGBoost. A Variance Inflation Factor (VIF) analysis was conducted to verify the absence of severe multicollinearity among the predictor variables. Based on performance evaluation, XGBoost was selected as the final model due to its superior predictive performance and stability, yielding an R² of 0.8712 on the 2025 test data and a mean 5-fold cross-validation R² of 0.7723. To enhance model transparency, SHapley Additive exPlanations (SHAP) was employed. Interpretation results revealed that Innovation Capability (Pillar 12), Adoption of Information and Communication Technology (Pillar 3), and Market Size (Pillar 10) are the most influential factors affecting regional competitiveness scores. Building on these findings, the developed system delivers context-specific, priority policy recommendations through an interactive dashboard. This study demonstrates that the integration of XGBoost and XAI constitutes a more objective, transparent, and adaptive data-driven decision-making solution for supporting regional competitiveness improvement in Indonesia.
Analisis Usability Sistem E-Voting Pemilihan Ketua dan Wakil Ketua OSIS dengan Metode Think Aloud Fajar Husain Asyari; Ellen Proborini; Sholihul Ibad
Jurnal Teknologi Terpadu Vol 12 No 1 (2026): Juli, 2026
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v12i1.2583

Abstract

The election of the OSIS (Student Council) chairman and vice-chairman is an important school agenda that requires a fast, accurate, and transparent voting process. With the advancement of information technology, e-voting systems have become a modern solution, but their success strongly depends on the system's usability. This study aims to evaluate the usability level of the e-voting system for the election of the OSIS (Student Council) president and vice-president using the Think Aloud method. The evaluation involved ten student respondents as the system’s target users, who were asked to complete six task scenarios—from entering the token to logging out—while verbalizing their thoughts and difficulties. The results showed that 90% of respondents successfully completed task scenarios T1–T5, while 60% encountered difficulties in task T6 (logging out). Based on the severity rating analysis, three main issues were identified: slow response time (score 4, critical), unclear navigation (score 3, major), and confusing input forms (score 3, major). Overall, the system achieved a task completion rate of 93.3% with an average completion time of 38 seconds per task. These results indicate that the e-voting system demonstrates good usability but requires improvements in navigation, system performance, and input guidance to enhance user experience. The Think Aloud method proved effective in directly identifying usability issues from the user perspective.
Co-Authors Aditya Hermawan Dwi Purnomo Putro Ellen Proborini Fajar Husain Asyari Sintha Istikomah