Perbandingan Metode Neural Network Model Radial Basis Function Dan Multilayer Perceptron Untuk Analisa Risiko Kredit Mobil - Amrin Amrin (LPPM Universitas Bina Sarana Informatika, 2018)
Problems are often encountered in the provision of credit is to determine lending decisions to someone, while other issues are not all credit payments can run well. Among the causes are errors of judgment in making credit decisions. In this study will be used neural network with radial basis function method and neural network with multilayer perceptron method to analyze the risk of car credit, then compare which method is the better. From the test results to measure the performance of the method is to use testing methods confusion matrix and ROC curve, it is known that the method of neural network with multilayer perceptron is better than method of neural network with radial basis function where has a value of accuracy is 96,1% and value of AUC is 0.999. This shows that the model produced, including the classification is Exellent Clasification because it has the value of AUC between 0.90- 1.00.