*Putri Fatimah Nurdin -  Kyushu University, Japan
Tetsuya Kubota -  Faculty of Agriculture, Kyushu University, 6-10-1 Hakozaki Higashi-Ku Fukuoka 812-8581, Japan, Japan
Received: 31 Jul 2017; Published: 25 Apr 2018.
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This study aimed to assess landslide susceptibility by employing certainty factors model (CF) to select the causative factors for landslide susceptibility mapping in Upstream of Jeneberang River, South Sulawesi. Indonesia. The landslide causative factors were: soil, slope angle, aspect, elevation, lithology, land use, distance to the river, drainage density, and precipitation. For validation purpose, landslide inventory map was randomly partition into two groups, 30% for the validation and 70% for the training. Landslide susceptibility maps were produced by logistic regression using original factor (all nine factors) and selected factor (four factors with positive CF value). The result of certainty factor analysis shows CF value is positive for elevation, land use, slope and drainage density. The accuracy of two landslide susceptibility maps were evaluated by calculating the area under the curve of Receiver Operating Characteristic (ROC) curves. The result shows the the success rate curve for nine factor map (80.2%)  is higher than four factor map (78%). But in case of closeness between success rate curve and predictive rate curve, certainty factors model has a closer distance. In this study, effect analysis studies show how the accuracy changes when the input factors are changed.

Landslide; Susceptibility Map; GIS; Certainty Factor; Logistic Regression

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