LANDSLIDE SUSCEPTIBILITY MODELING USING WOE-RF-SBS (WEIGHT OF EVIDENCE-RANDOM FOREST-WITH SPATIALLY BALANCED SAMPLING) METHOD BASED ON MACHINE LEARNING AND BIVARIATE STATISTICAL ANALYSIS (CASE STUDY: CISANGKUY SUB-WATERSHED)
Landslide susceptibility modeling (LSM) is necessary as an initial effort in disaster mitigation. State of the art in study of LSM is an integrated method of bivariate statistics and machine learning. In machine learning-based modeling, the response variable has two classes, i.e., landslide presence...
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| Format: | Dissertations |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/70973 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |