Optimization of institutional framework for mangrove ecosystem management in Jakarta Bay: A multi-stakeholder collaborative approach

Abstract

This study explores the optimization of institutional frameworks for managing the mangrove ecosystem in Jakarta Bay, a complex social-ecological system requiring effective management across multiple jurisdictions. The research employs integrated DPSIR (Drivers, Pressures, State, Impact, Response), MICMAC (Matrix of Cross-Impact Multiplications Applied to Classification), and MACTOR (Matrix of Alliance and Conflict: Tactics, Objectives, and Recommendations) approaches. Data was collected between October 2023 and January 2024 from stakeholders in three provinces: Banten, DKI Jakarta, and West Java. The study used field observations, structured interviews, focus group discussions, and secondary data, including remote sensing analysis of Landsat 8 and Sentinel-2 imagery (2013-2023). Findings reveal five driving forces, four pressures, two states, seven impacts, and six responses through DPSIR analysis. MICMAC identified four key factors influencing mangrove management: monitoring system implementation, biodiversity levels, ecosystem health, and extreme event frequency. MACTOR analysis of 19 stakeholders shows central government actors possess high influence but low dependence, while regional governments, the private sector, and local communities display varying influence and high dependence. The study proposes four strategic approaches for institutional optimization: (1) Determinant-Driver Factors, (2) Autonomous-Divergence, (3) Influential-Convergence, and (4) Influential-Intermediate Convergence. The optimal structure recommends the Jakarta Bay Mangrove Management Forum (FPMTJ) for coordination and the Jakarta Bay Mangrove Management Agency (BPMTJ) for implementation. Comparative analysis indicates significant improvements in institutional performance, with average scores rising from 2.3 to 4.2, demonstrating better coordination, reduced task duplication, enhanced adaptability, and faster decision-making (1-2 months).