AI-Assisted B2G Cloud Intelligence Simulation for Foundational Digital Governance Competencies: A Pilot Study in Higher Education
Digital governance increasingly requires future managers to understand integrated data, policy gaps, cloud-based information systems, and evidence-based recommendations. This study evaluates B2G Cloud Intelligence, an AI-assisted cloud-based simulation platform designed to support foundational digital governance competencies in higher education. The study involved Management Study Programmeme students at the State University of Malang enrolled in a Management Information Systems course. Of 72 participants, 68 valid data sets were analyzed over a four-week trial covering platform orientation, Helicopter View, Data Integration, Policy Insight, AI Consultant, Gap Analysis, and Policy Map development. Data were collected through pre-test and post-test, Technology Acceptance Model (TAM)-based usability questionnaires, and project output assessment rubrics. The results show that the average score increased from 60.3 to 81.7, with a gain of 21.4 points. The TAM score reached 4.22, and project output assessment achieved 86.1 out of 100. These findings provide preliminary evidence that AI-assisted B2G simulation can support foundational competencies related to data integration, policy analysis, and evidence-based recommendation formulation. However, due to the one-group pilot design, the findings should not be interpreted as causal evidence of labour-market outcomes or public-sector performance.
Authors
- Ari Gunawan (ORCID: https://orcid.org/0000-0002-4074-7200)
- Afis Baghiz Syafruddin (ORCID: https://orcid.org/0000-0001-9079-4235)
- I Nyoman Suputra (ORCID: https://orcid.org/0009-0006-4898-3108)
- Andi Basuki (ORCID: https://orcid.org/0000-0002-1564-4349)
- Subagyo Subagyo (ORCID: https://orcid.org/0009-0008-3611-8007)
Institutions
- State University of Malang (ID)
- Universitas Gadjah Mada (ID)
Publication Details
- Journal
- Economies
- Published
- 2026-09-01
- DOI
- https://doi.org/10.3390/economies14090362
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universitas Negeri Malang