Abstract

Disaster is an event or a series of events that threatens and disrupts people's lives and livelihoods, caused by natural and/or non-natural factors and human factors, resulting in human casualties, environmental damage, property losses, and psychological impacts. Hydrometeorological disasters are events related to water, atmosphere, and oceans. It is recorded that hydrometeorological disasters occurring in Indonesia reach 86%, including floods, tornadoes, landslides, forest and land fires, and droughts. Specifically, in Central Kalimantan Province, forest and land fires and floods are frequent disasters. Both fall into the category of hydrometeorological disasters, closely related to the climate in Central Kalimantan. In this study, the prediction of rainfall, temperature, and humidity values in Central Kalimantan Province was calculated using the Auto-Regressive Integrated Moving Average method at 5 stations in the province. Subsequently, the prediction analysis of flood events was carried out using the machine learning random forest method based on the rainfall data, temperature, humidity, and event data. According to the calculation results, flood disasters are not predicted to affect almost all areas of Central Kalimantan Province. However, by the end of 2023, it is anticipated that most areas in the province will still be categorized as experiencing a normal level of drought. Notably, there are two areas that must increase awareness of this drought disaster, namely Pulang Pisau and Sampit, especially in October 2023.

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