Analisa Kelayakan Pemberian Kredit Mobil Dengan Menggunakan Metode Neural Network Model Radial Basis Function - Amrin Amrin (Paradigma, 2017)
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 to analyze the feasibility of providing car loans. 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 back neural network radial basis function has a value of 89,2% accuracy and AUC value of 0.9471. This shows that the model produced, including the classification is Exellent Clasification because it has the AUC values between 0.90- 1.00.