INTEGRATING SPATIAL POLICY, INFRASTRUCTURE DESIGN, AND EVALUATIVE TECHNOLOGY IN DISASTER RISK REDUCTION FOR VOCATIONAL EDUCATION: A BIBLIOMETRIC AND SYSTEMATIC LITERATURE REVIEW
Abstract
Purpose - Vocational education is highly vulnerable to disasters; however, current mitigation strategies are fragmented across spatial planning regulations, infrastructure design, and assessment technologies. This study seeks to carefully examine the evolution of Disaster Risk Reduction (DRR) research within vocational education, finding trends, knowledge frameworks, and research deficiencies, while also developing a cohesive transdisciplinary framework.
Methodology - The study employs a synthesis of bibliometric analysis and Systematic Literature Review (SLR), adhering to the PRISMA 2020 guideline. The search was conducted in the Scopus database for the period 2004–2024, yielding 162 initial documents, which were further refined to 16 core papers using rigorous selection criteria. Bibliometric analysis encompasses publishing trends, keyword co-occurrence, and co-citation, utilizing bibliometrics and VOSviewer.
Findings - Publications increased by 18% per year, with the Asia-Pacific region dominating (62%). Three thematic clusters were identified: adaptive infrastructure design (43.75%), spatial planning policy (31.25%), and geospatial information systems (25%). Co-citation analysis confirms that no single influential document integrates all three dimensions simultaneously within the context of vocational education.
Contribution - The study formulates a transdisciplinary framework that integrates technical, spatial, and technology-based resilience within vocational education. The implications include strengthening national standards (SNI) for school buildings, integrating Geographic Information Systems (GIS) into the construction vocational school curriculum, and fostering institutional partnerships between the Ministry of Education, Culture, Research, and Technology and the National Disaster Management Authority to support region-based risk management.Keywords
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DOI: https://doi.org/10.36987/jes.v13i3.9261
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