An Integrated AHP–TOPSIS Model to Enhance the Effectiveness of Disaster Logistics Distribution (Case Study: Regional Disaster Management Agency of Minahasa)

Abstract

Abstract: This study is motivated by the challenges faced by the Regional Disaster Management Agency (BPBD) of Minahasa Regency in determining the priority of disaster logistics distribution in a rapid, accurate, and objective manner under constraints of limited resources and time, where decisions often rely on manual processes that are susceptible to subjective bias. The objective of this study is to design and implement an integrated model of the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a Disaster Logistics Management Information System to support structured and measurable decision-making. The research method involves the development of an AHP–TOPSIS integration model, in which AHP is utilized to determine the weights of priority criteria, while TOPSIS is applied to generate a ranking of affected areas based on priority levels. The findings indicate that the integrated AHP–TOPSIS-based system enhances the objectivity and accuracy of logistics distribution decisions, making them data-driven and grounded in accountable mathematical calculations. The implementation results demonstrate that this approach effectively addresses the limitations of manual decision-making, producing consistent and accountable aid allocation decisions. In conclusion, the AHP–TOPSIS integration model serves as a significant strategic solution in improving the effectiveness, targeting accuracy, and efficiency of aid distribution processes at BPBD Minahasa. It is recommended that the application of this method be further developed by adapting it to the specific needs and geographical conditions of affected areas, as well as ensuring data accuracy to maintain the validity of priority analysis results..