Didik Taryana, Rudi Hartono, Dicky Arinta, Agus Purnomo, Ike Sari Astuti
Landslide is one of the disasters that often occurs in Indonesia in the East Java Province, especially in Bendun-gan District, Trenggalek Regency. Analysis of landslide susceptibility in Bendungan District is needed to spatially locate the landslide occurrences. The purpose of this study was to predict landslide events using an artificial neural network. Rainfall, topography, physical soil properties, and land-use were used as the explanatory variables. An analytic hierarchy process approach was applied to determine the weight of the variables. The model satisfactorily classified the landslide hazards with an area under curve of 0.96. The northwest area of the Bend-ungan District was found to be a region at high risk with rainfall and soil texture as the most influential parts in triggering the landslides. © 2023, Kauno Technologijos Universitetas. All rights reserved.
Department of Geography, Faculty of Social Sciences, State University of Malang, Indonesia; Department of Social Sciences, Faculty of Social Sciences, State University of Malang, Indonesia
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