Fuzzy Logic Clustering Modeling of Surface Soil Parameters Based on Georesistivity Profiles and Geology Techniques

Abstract

This research generally aims to develop a model that can simplify and streamline the investigation of surface soil work in particular knowing the characteristics of soil layers based on electrical resistivity. Problems that occur many construction failures are caused by exploitation of land use that exceeds the carrying capacity of the land, for example, the use of land originating from peat, swamps or lakes which often occurs land suddenly. Therefore, to achieve accurate soil data, a good soil investigation is needed and a georesistivity method can interpret soil properties and determine stratigraphy and characteristics of soil layers. The qualitative and quantitative research methods used consist of field research based on soil resistivity values and laboratory investigations that use conventional soil investigations as a comparison and as a reference to get detailed results on the soil layer while the results obtained from measurements on the georesistivity profile to a depth of 15 m. Testing the results of engineering geological drilling to a depth of 15 m, obtained 4 types of soil CH, CL, MH and ML. The results are in clusters using artificial intelligence algorithms and formed into 4 clusters which in total have 47 members.