Pemetaan Kerawanan Longsor Berbasis Sistem Informasi Geografis pada Daerah Kikim Selatan, Kabupaten Lahat, Sumatera Selatan

Wulandari Wulandari; Budhi Setiawan; Dede Nurohim

doi:10.37905/geojpg.v5i1.38967

Pemetaan Kerawanan Longsor Berbasis Sistem Informasi Geografis pada Daerah Kikim Selatan, Kabupaten Lahat, Sumatera Selatan

Wulandari Wulandari, Budhi Setiawan, Dede Nurohim

Abstract

The South Kikim Area, South Sumatra, is characterized by hilly terrain, weathered sedimentary lithology, steep slopes, and geological structures that may increase landslide susceptibility. These conditions highlight the need for spatial information on landslide-prone areas to support disaster mitigation and regional planning. This study aims to map landslide susceptibility and identify the controlling factors in the South Kikim Area. The analysis employed a Geographic Information System (GIS)-based weighted scoring method by integrating geological conditions, slope gradient, soil type, and land cover parameters. Each parameter was assigned a score and weight according to its contribution to slope instability and then analyzed through spatial overlay techniques to produce a landslide susceptibility map. The results indicate that the study area of 8,057.58 ha is classified into three susceptibility levels: low susceptibility covering 48.40 ha (0.60%), moderate susceptibility covering 7,064.09 ha (87.67%), and high susceptibility covering 945.10 ha (11.73%). High-susceptibility zones are concentrated in the southern part of the study area, particularly in Pseksu District, and are associated with calcareous shale, weathered claystone, and steep to very steep slopes. Lithology and slope gradient were identified as the dominant factors controlling landslide susceptibility distribution. The resulting susceptibility map can serve as a reference for disaster mitigation and spatial planning in the study area.

Keywords

Landslide Susceptibility; Geographic Information System; Weighted Scoring; Susceptibility Zoning; Disaster Mitigation

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DOI: https://doi.org/10.37905/geojpg.v5i1.38967

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