Multi-Criteria Decision Support System for Flood Alert Classification in Smart Cities

People unfamiliar with flood status often find it difficult to understand complex information such as flood warnings from authorities. Decision support systems can process this information and provide more superficial, more understandable reports to the public so they can respond correctly. This research proposes the development of a Multi-Criteria Decision Support System for Flood Warning Classification in smart cities. Identifying flood alert status includes safety, alert, warning, and watchful to improve preparedness and response to flood hazards in a city. The TOPSIS method was used as the main framework in this study to evaluate flood-related data using rainfall parameters, water table height, water discharge, tides, temperature, and humidity. In the decision-making process, TOPSIS will produce a ranking that allows for determining the flood alert status that best suits the actual conditions on the ground. Based on the research results regarding the classification of flood alert status, watchful status dominates, with the highest score of 0.929. This is followed by the alert status, which occupies the second position with a score of 0.193. Furthermore, the warning status is ranked third with a score of 0.185. Meanwhile, the safe status occupies the last position, namely the fourth rank, with a score of 0.070.