Main Article Content
The percentage of non-performing financing in BMT Al Munawwarah at 2016 exactly high for every month, so should be taken a method to predict the quality of financing before filing a customer applicant approved. An Artifical Neural Network (ANN) is processing of information system has characteristic similar biology neural network, ANN used to predict because the good approachment ability toward unlinear. This research attempts to design software to predict the quality of financing with the ANN method. Based on the results of training with training datasets 276 data and validation datasets 91 data, using architecture with 1 hidden layer and 164 neurons, iteration 2000, and retrain 10 times, produce results the accuration of application 82%. With the test datasets 91 data, applications can recognize the test datasets about 75 data. Based on these results, ANN can be used to predict the quality of financing.
Huda, N. 2016. Baitul Mal Wa Tamwil: Sebuah Tinjauan Teoritis. Jakarta: Amzah.
Sudarsono, H., 2003. Bank dan Lembaga Keuangan Syariah. Yogyakarta: Ekonisia.
Hermawan, A., 2006. Jaringan Saraf Tiruan, Edisi 1. Yogyakarta: Andi Offset.
Suprawoto, T., & Bintoro, A.R., 2014. Implementasi Jaringan Saraf Tiruan dengan Metode Backpropagation Untuk Prediksi Kelayakan Kredit di BMT Beringharjo. Tesis, Amikom Yogyakarta.