Risk Management in Community Service: An Integrated Approach to Addressing Social Challenges in Communities - CNAWP, Rizal Perlambang; Basir, Badirun; Yusda, Desi Derina; Nofirman, Nofirman (Journal Of Human And Education (JAHE), 2025)
Community service programs often operate in complex environments where social, economic, and cultural factors intersect, creating diverse risks that threaten their effectiveness and sustainability. This study explores an integrated approach to risk management in community service, combining principles from ISO 31000 with community-based participatory methods. Using a qualitative multi-case study design, data were collected through semi-structured interviews, focus group discussions, and document analysis across 17 community programs in Southeast Asia from 2020 to 2024. The findings highlight key risk categories, including volunteer safety incidents, funding discontinuities, cultural misalignment, and data privacy breaches. Programs employing integrated risk management strategies demonstrated significant improvements in risk preparedness and mitigation outcomes. For instance, preventive measures such as GPS tracking for volunteers and diversified donor portfolios reduced preventable incidents by 37% and enhanced program continuity. Additionally, participatory approaches involving community advisory boards identified 22% more contextual risks compared to top-down methods. This study proposes a five-phase implementation model emphasizing stakeholder collaboration, adaptive monitoring, and real-time feedback loops to address dynamic risks effectively. The results underscore the importance of embedding risk communication, prioritizing resources strategically, and fostering cultural brokerage to enhance program resilience. By aligning theoretical frameworks with practical applications, this research provides actionable insights for policymakers and practitioners seeking to harmonize risk management with social impact goals. Future studies should explore the long-term cost-effectiveness of participatory models and the potential of AI-driven risk prediction tools in resource-constrained settings. This integrated approach offers a pathway to more sustainable and impactful community service initiatives.