CD Skripsi
Analisis Sifat Fisik Yang Paling Berpengaruh Terhadap Koefisien Permeabilitas Tanah Kohesif Menggunakan Artificial Neural Network
ABSTRACT
The permeability coefficient is a significant soil parameter in seepage calculations. Permeability is also related to the physical properties of the soil. Of the several soil physical properties, there is one soil physical property that has the most influence on the permeability coefficient. This can be determined by using artificial intelligence which is capable of imitating the human nervous system, one of which is using an Artificial Neural Network which has the advantage of modeling complex relationships. This research will be carried out to determine the physical properties that most influence the permeability coefficient using artificial intelligence, namely the Artificial Neural Network. The research method will be carried out in 3 stages, namely Training, testing, and simulation. The amount of data used is 80 data with 3 variations, namely the 50:50 variation, the 60:40 variation, and the 70:30 variation. Determination of the most influential physical properties can be seen from the R value which is close to 1. The inputs used are Liquid Limit, Plastic Limit, Plasticity Index, %Sand, %Fines, %Silt, and %Clay using a single input - single output. In this study it can be concluded that of the 7 input parameters, the one that has the most influence on the permeability coefficient is %Fines with an average R value of 0.99263, MSE value of 4.1393E-12, R2 value of 0,9475, and MAPE value of 0,3038% found in variation A.
Keywords: Permeability, Soil Physical Properties, Artificial Intelligence, Artificial Neural Network, Backpropagation.
Tidak tersedia versi lain