Website-Based Application for Flood Event Prediction Using Machine Learning Method In Cilacap District

Imam Tahyudin, Faiz Ichsan Jaya, Nur Faizah


Floods are the most common natural disasters, both in terms of their intensity at a place and the num- ber of locations of events in the amount of 40% among other natural disasters. The impact of flooding on the area in general is temporary housing in rural areas caused by flooding in addition to settlement as well as agriculture which can have an impact on the food security of the area and also a national level that is higher than the magnitude of the country. Based on data from the Central Statistics Agency of Cilacap Regency, the number of flood victims in Cilacap Regency in 2018 reached 771 people and arranged for them to flee from the flood. To solve this problem, do research to create a web-based application using the classification of the Support vector machine or Random Forest to predict flood events and compare the accuracy values of the two algorithms to get better prediction results.


Website; Machine Learning; SVM; Random Forest

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