The current centralized system is vulnerable to data manipulation due to the absence of independent verification mechanisms, thereby compromising the reliability of information. In addition, the inconsistency of formats and data silos across agencies exacerbates information fragmentation. Delays in data distribution hamper rapid response in emergency situations, while uneven communication infrastructure—especially in remote areas—reduces real-time monitoring capabilities. Lack of coordination among stakeholders—such as BNPB, forestry agencies, local communities, and the private sector—adds to the complexity of disaster management and often leads to overlapping tasks. The decision-making process is further complicated by competing criteria, such as priority areas, resource availability, dynamic weather conditions, and limited IoT sensor coverage. Additionally, high operational costs for system maintenance and limited audit trails make it difficult to track data history and ensure accountability. Therefore, the Multi-Criteria Decision Making (MCDM) method is necessary to handle uncertainty, combine different geospatial factors in an organized way, and make sure the decision-making process is reliable and clear. This research fills the technological gap by introducing a decentralized audit trail while facilitating cross-sector collaboration in fire mitigation decision-making and minimizing the risk of evidence-based data errors.
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