Spatial Decision Support System to Determine the Feasibility of Evacuation Posts in Natural Disasters - Alviola, Nuril Afni; Almais, Agung Teguh Wibowo; Syauqi, A’la; Chamidy, Totok; A Basid, Puspa Miladin Nuraida Safitri; Anisa, Anisa; Wardana, M. Dafa (UIN Sunan Kalijaga Yogyakarta, 2025)
This study aimed to improve the accuracy of determining the feasibility of evacuation posts after natural disasters using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within a Spatial Decision Support System (SDSS). A dataset of 50 evacuation posts from the 2021 Mount Semeru eruption was analyzed. The Rank Order Centroid (ROC) method was applied for criteria weighting, and TOPSIS was used to process the data. Results showed 72% accuracy, confirming that TOPSIS is a passable method for assessing post-feasibility based on accessibility, sanitation, and refugee facilities. Although the focus is on evaluating post-disaster evacuation posts, the system can be adapted for use in various other types of disasters. However, it is still dependent on historical data and lacks real-time adaptability. Future research can integrate Artificial Intelligence (AI) and Machine Learning (ML) with real-time data to improve decision-making in disaster management.