Social and Economic Impacts of the Disaster-Resilient Village Program with Bayesian Decision-Making

This study evaluates the social and economic impacts of the Disaster-Resilient Village (DRV) Program using Bayesian Decision-Making. Conducted in Pekalongan City, a region frequently affected by tidal flooding and coastal erosion, this research employs a quantitative approach to assess the program’s effectiveness in enhancing disaster resilience. The study involves 563 respondents, including 18 government officials and 545 affected community members, selected through purposive and proportional sampling. Data were collected through structured surveys measuring disaster preparedness, economic losses, and financial accessibility. Bayesian probabilistic modeling was applied to analyze decision-making patterns in disaster risk reduction and to optimize resource allocation strategies. The results indicate that financial aid and credit accessibility significantly accelerate economic recovery, while disaster preparedness alone does not directly influence resilience. Infrastructure damage, however, prolongs recovery time, underscoring the need for resilient infrastructure investments. These findings highlight the importance of integrating financial mechanisms into the DRV framework to enhance economic stability post-disaster. Policymakers should prioritize expanding financial aid programs, improving credit accessibility, and strengthening infrastructure resilience to minimize long-term economic disruptions. Future research should incorporate longitudinal studies and explore the role of social factors in disaster recovery to provide a more comprehensive analysis.