Identification Comparison of Landslide Potential Area with Analytical Hierarchy Process and Logistic Regression Methods in Cisarua District and Surroundings, Bogor Regency, West Java

Agun Romdha Sastra Pratama; Misbahudin

doi:10.25299/jgeet.2025.10.1.1.24031

Authors

Agun Romdha Sastra Pratama Universitas Pertamina, Department of Geological Engineering, Jalan Teuku Nyak Arief, Jakarta, 12220, Indonesia
Misbahudin Universitas Pertamina, Department of Geological Engineering, Jalan Teuku Nyak Arief, Jakarta, 12220, Indonesia

DOI:

https://doi.org/10.25299/jgeet.2025.10.1.1.24031

Keywords:

Landslide, Analytical Hierarchy Process (AHP), Logistic Regression (LR), Confusion Matrix

Abstract

Landslide is one of the geological disasters that often occur in Indonesia, especially in Cisarua District and its surroundings, Bogor Regency, West Java, so mitigation activities need to be carried out, one of which is by making a map of potential areas of landslide in the research area. This study aims to analyze the spatial distribution of potential landslides in Cisarua District, Bogor Regency, using the Analytical Hierarchy Process (AHP) and Logistic Regression (LR) methods, and to determine the more effective method for landslide prediction in the study area. The results showed that the AHP method obtained the distribution of potential areas of landslide in the low category with an area of 39,592 km² with a percentage of 38.99%, the moderate category with an area of 39,690 km² with a percentage of 39.09% and the high category with an area of 22,253 km² with a percentage of 21.92%. In the LR method, the potential for landslide was obtained in the low category with an area of 39,158 km² with a percentage of 38,15%, the moderate category with an area of 39,485 km² with a percentage of 38.86%, and the high category with an area of 22,967 km² with a percentage of 23% and the best method in determining the potential area of landslide was the LR method with an overall accuracy level of 86.41% compared to the Analytical Hierarchy Process (AHP) method with an overall accuracy of 78.64%.

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