<![CDATA[One of the natural disasters that often occurs is landslides. Factors that cause landslides are geology, vegetation density, slope, slope direction, lithology type, and rainfall. Also related to the human factor in terms of land use. The case study of this research is Suliki District. The help of the Python programming language in GIS is able to create a model that aims to lighten and simplify the steps of spatial analysis. To create a landslide susceptibility model, the researchers used the Weight of Evidence (WoE) weighting method. The data used in this study were 30 random ground motion events. The data is divided into two groups of data, 60% is used as analysis data that functions for the preparation of the model and 40% is used as validation data for model testing. The research procedure includes the weighting of eight parameters that are considered as triggers for landslides. The results of the model test show the AUC value of 0.82. The use of Python programming language with bivariate statistical methods can run well according to the expected results.]]>
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