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All Journal Liquidity: Jurnal Riset Akuntansi dan Manajemen
Siti Chodijah
Mahasiswa Pascasarjana Keuangan Syariah STIE Ahmad Dahlan Jakarta
Economics, Econometrics & Finance

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Implementasi Artificial Neural Network Dalam Memprediksi Pembiayaan Bermasalah Pada BMT Al Munawwarah Siti Chodijah; Saiful Anwar
Liquidity: Jurnal Riset Akuntansi dan Manajemen Vol 7 No 1 (2018)
Publisher : Institut Teknologi dan Bisnis Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/lq.v7i1.177

Abstract

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.
Co-Authors Saiful Anwar