<![CDATA[Many regional disaster management agencies still manage incident reporting through conventional, semi-manual workflows (e.g., spreadsheets and paper archives). These practices often create repetitive recapitulation tasks, increase the likelihood of data inconsistency, and produce reports that remain largely descriptive—limiting analytical support for timely, evidence-based decision-making. To address this limitation, this study develops a web-based disaster reporting and recapitulation system integrated with the Simple Additive Weighting (SAW) method to generate an event-level Impact Index for prioritization. The system is built using a Prototyping approach, enabling iterative refinement through user feedback to ensure operational fit. SAW is applied using weighted criteria—number of casualties, affected families, damage level, and disaster type—so that each recorded event can be scored and ranked automatically. In contrast to many prior disaster-related SAW applications that emphasize beneficiary selection or aid distribution, this research applies SAW for internal managerial evaluation, prioritizing disaster events themselves to support organizational review and mitigation planning. A case study at BPBD Minahasa Regency demonstrates the system’s feasibility and performance: Black Box Testing achieved a 100% functional success rate, and manual SAW verification confirmed that automated Impact Index outputs are mathematically consistent with theoretical calculations. Overall, the proposed application offers a structured and transparent analytical tool to standardize reporting, accelerate recapitulation, and strengthen decision support through objective impact-based ranking.]]>
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