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All Journal Journal of Government Science (GovSci ) : Jurnal Ilmu Pemerintahan Indonesian Governance Journal : Kajian Politik-Pemerintahan
Yujitia Ahdarrijal
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Social Sciences

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Openness In Governance: The Effect of the E-Government Index on Regulation Quality in Australia Anggita, Irva; Endang Indri Listiani; Yujitia Ahdarrijal
JOURNAL OF GOVERNMENT SCIENCE Vol 6 No 1 (2025)
Publisher : Program Studi Ilmu Pemerintahan Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54144/govsci.v6i1.109

Abstract

This research explores the relationship between the E-Government Development Index (EGDI) and the Quality of Government Regulation in Australian states. This study uses a quantitative approach with exposure to literature studies through Scopus and analyzes primary and secondary data. This research produced Online Service Index (OSI) p-values (0.388), E-Participation Index (EPI) p-values (0.764), Human Capital Index (HCI) p-values (0.000), and Telecommunication Infrastructure Index (TII) p-values (0.000) as predictors of Regulatory Quality (RQ). The use of the Smart PLS version 3 method and reliability and validity tests demonstrate the reliability of the proposed model. Statistical analysis yielded interesting results: EPI and OSI had no significant effect on RQ, while HCI and TII had a positive and significant relationship. These results provide insight into the factors influencing Regulatory Quality in the context of E-Government in Australia, supporting policy development to improve the efficiency and quality of public services. The research also contributes to an understanding of the impact of EGDI on governance and regulation at the state level.
UTILIZING BIG DATA AND ARTIFICIAL INTELLIGENCE TO MONITOR SDG ACHIEVEMENTS Herpita Wahyuni; Yujitia Ahdarrijal; Nur Syakiran Akmal Ismail Syakiran Akmal Ismail
INDONESIAN GOVERNANCE JOURNAL : KAJIAN POLITIK-PEMERINTAHAN Vol 9 No 1 (2026)
Publisher : Universitas Pancasakti Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24905/igj.v9i1.171

Abstract

This study aims to formulate a Big Data and Artificial Intelligence (AI)-based model for monitoring the SDGs within a data-driven governance framework. Using a descriptive qualitative approach and a conceptual study, the study focuses on four aspects: current monitoring mechanisms, potential Big Data-based data sources, opportunities for AI utilization, and data governance and inter-agency interoperability. Data were obtained from literature reviews, policy documents, and news sources on the implementation of the SDGs, Big Data, AI, and data governance. The results show that the weakness of SDGs monitoring lies not in the availability of indicators or data, but rather in the monitoring and governance architecture, which remains administrative, periodic, and sectoral, resulting in slow information flow and minimal analytics. Abundant data sources actually meet the characteristics of Big Data, and AI can transform indicator readings into real-time, analytical, and predictive insights. However, their utilization has not been optimal due to interoperability constraints and procedural data governance. Monitoring transformation requires the integration of Big Data, the use of AI, and a shift in governance towards interoperability across agencies. Further research suggestions include the empirical testing of the model through case studies in local governments/agencies, the development of a Big Data and AI-based monitoring dashboard prototype, and the measurement of its impact on the quality of policy-making
Co-Authors Anggita, Irva Endang Indri Listiani Herpita Wahyuni Nur Syakiran Akmal Ismail Syakiran Akmal Ismail