GEOSPATIAL MODEL OF LANDSLIDE POTENTIAL USING RANDOM FOREST THROUGH GOOGLE EARTH ENGINE PLATFORM IN SUKAMAKMUR DISTRICT, BOGOR REGENCY
DOI:
https://doi.org/10.53840/ejpi.v12i5.324Keywords:
Google Earth Engine; Landslide; Random Forest; Spatial AnalysisAbstract
This research aims to map the potential landslide disaster in Sukamakmur Sub-district, Bogor Regency, using Random Forest method through Google Earth Engine platform. Sukamakmur Sub-district is an area with a high risk of landslides due to high rainfall and steep topographic conditions. The Random Forest method was chosen due to its ability to handle complex data and produce accurate predictions. In this study, the data used include slope, Topographic Wetness Index (TWI), distance from river, soil texture, rainfall, geological type, and land cover, which were processed using Google Earth Engine platform. The results showed that the Random Forest model was able to map landslide potential in Sukamakmur Sub-district with high accuracy. The model successfully identified areas with very high, high, medium, low, and very low landslide potential. The area included in the very high landslide potential category reached 1,331.39 Ha, while the high category covered 8,524.05 Ha. The most contributing factors in predicting landslides are slope and rainfall. This research contributes to disaster mitigation efforts by providing accurate landslide potential maps. The results can be used by the Regional Disaster Management Agency (BPBD) of Bogor Regency as a basis for decision-making in an effort to reduce the risk of landslides in Sukamakmur Sub-district.
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