<![CDATA[One of the areas in Batu Bara Regency, Pahlawan Village, Tanjung Tiram District, has an area of ??173.79 km² and is located in a lowland area with an altitude of 0.-4.5m which is directly adjacent to the Malacca Strait to the east. Where almost half of the area is affected by sea tides, Hero Village has a tropical climate with two seasons namely the rainy season and the dry season. The people who live in Pahlawan Village, Tanjung Tiram District. There are so many obstacles faced by the people of Pahlawan Village, including the problem of flooding which has an impact on the health and the economy of the community. Lack of counseling and knowledge, as well as public awareness of the occurrence of flooding during high tides, and when the rainy season will increase the water discharge at sea level will rise so that it can cause flooding. In this study, the implementation of machine learning was used as a mapping system for flood-prone areas in Pahlawan Village, Batu Bara District, with data analysis used using primary and secondary data, both qualitative and quantitative. Due to the occurrence of floods, and the impact of losses that affect material and non-material, it is very important to map flood-prone areas for regional development planning. Identification of potential flooding involves machine learning using the Random Forest method, taking into account the triggering factors for flooding. The Random Forest method also provides sensitivity parameters using a Receiver Operating Characteristic (ROC) curve which indicates areas prone to flooding, for example, Pahlawan Village, Tanjung Tiram District]]>
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