Bayesian Networks to Support National Policy Decision Making in Indonesia: A Literature Review
Abstract
Bayesian Networks (BNs) offer a promising solution for addressing the complexities of public policy decision-making in Indonesia, characterized by uncertainty and diverse factors. As probabilistic graphical models, BNs provide a structured framework to integrate various aspects—social, economic, environmental, and cultural—into policy formulation. This research explores the potential and opportunities for implementing BNs as an effective decision-making tool for national policies through a systematic literature review. The findings highlight the adaptability of BNs in modeling complex systems, enabling policymakers to simulate scenarios, evaluate trade-offs, and design evidence-based strategies. Applications in Indonesia, such as aquaculture management in Lake Maninjau, demonstrate the capacity of BNs to balance ecological sustainability with socio-economic needs. Moreover, BNs address uncertainties in water resource management, poverty reduction, and environmental risk management, making them an essential tool for adaptive governance. By adopting BNs, Indonesia can enhance the inclusivity, precision, and resilience of public policies, ensuring better alignment with national development priorities. This research underscores the value of BNs in fostering holistic and effective decision-making frameworks, contributing to improved governance and sustainable outcomes in a dynamically evolving landscape.
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DOI: https://doi.org/10.21107/pamator.v19i1.28755
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