<![CDATA[One of the threats that can endanger society is extreme hydrometeorological disasters, especially in cities with high construction activity and population density. Due to weather changes and local environmental characteristics, Medan City, one of the major cities in Indonesia, is vulnerable to hydrometeorological events such as floods, extreme rainfall, strong winds, and puddles. This study uses the Random Forest algorithm and purposive sampling technique to classify the likelihood of extreme hydrometeorological disasters in the city of Medan. The data used is based on specific criteria relevant to disaster potential indicators, such as topographic conditions, land use, population density, and rainfall. The Random Forest method is used because it can process data with many variables and make accurate classifications through the combination of several decision trees. The research results are expected to classify the areas of Medan City based on their disaster potential: low, medium, or high. This category can be used as a basis for spatial planning, mitigation strategies, and decisions made by the government and relevant parties to reduce the risk of hydrometeorological disasters in the City of Medan.]]>
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