Data Driven Approach for Agromafia Risk Mitigation in Indonesia Using Blockchain and Advanced Analytics

Agromafia, a form of organized crime infiltrating the agricultural sector, poses significant threats to food security, market integrity, and economic stability in Indonesia. This study investigates the potential of technological intelligence-specifically blockchain, data analytics, and AI-driven surveillance-to prevent agromafia activities in Indonesia. Through a mixed-methods research design, the study integrates insights from international case studies, field surveys, expert interviews, and pilot implementations of technological frameworks. The results demonstrate that blockchain significantly enhances supply chain transparency, while predictive analytics and AI surveillance effectively detect and prevent criminal activities. The findings highlight the importance of multi-agency collaboration and a supportive regulatory framework to ensure the successful deployment of these technologies. This research provides a comprehensive strategy for leveraging technological intelligence to secure Indonesia's agricultural sector, drawing on lessons from Italy's fight against agromafia. The study contributes to the broader discourse on food security and market integrity, offering practical solutions for policymakers, law enforcement, and agricultural stakeholders in developing economies.