Abstract
Landslides is one of the most detrimental natural disasters because their occurrences are often destructive to natural and artificial structures on earth and reduce the quality of the surrounding environment. Prediction of the level of vulnerability to landslides in an area can be used to reduce losses caused such as material, loss of life and other environmental damage. BPBD Batu City stated that landslides are the most frequent disasters in Batu City. This research is expected to determine the level of vulnerability to landslides in Batu City, East Java and discover the correlation with the land use. Random Forest (RF) is an algorithm that can be used to predict landslide disasters. The disaster occurance data is then linked to the parameters that cause landslides such as slope, rainfall, soil type, lithology, land use, and soil movement susceptibility zones. The dataset is then divided into 70% training data and 30% testing data. The performance test results show that the RF algorithm can be applied to predict landslide-prone areas in Batu City. This can be seen in the results of the accuracy test which obtained a value of 0.8981 and an AUC value of 0.9327. The result shows that the high prone areas are in settlements, industry & public facilities while the low prone areas are in forest.
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