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All Journal Liquidity: Jurnal Riset Akuntansi dan Manajemen
Saiful Anwar
STIE Ahmad Dahlan Jakarta
Economics, Econometrics & Finance

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Penerapan Cadangan Kerugian Penurunan Nilai, Pendapatan Murabahah Dan Kinerja Keuangan Pada Bank Umum Syariah Tahun 2014 Muji Suhartini; Saiful Anwar
Liquidity: Jurnal Riset Akuntansi dan Manajemen Vol 5 No 2 (2016)
Publisher : Institut Teknologi dan Bisnis Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/lq.v5i2.52

Abstract

Provision Impairment Loss (CKPN) is allowance for value assets after there is an impairment less than the beginning balance. The calculation of CKPN is divided into two methods, they are individual and collective. The researcher used analysis as instrument of the research, that was structural equation modeling (SEM). The research was examined the effect of CKPN to Murabahah Income and Financial Performance that consists of four variables, they are NIM/NCOM, NPF, ROE, and ROA. The researcher used the data from 11 General Syariah Bank in 2014. The researcher used SEM method with alternative Partial Least Square (PLS) and used SmartPLS 1.0 application. The result showed that CKPN was effected for the level of Murabahah Income and Financial Performance at General Syariah Bank in 2014. The statistical result of the first hypnotical test was 0,951 with T-Statistic 55,884, it meant that those number was more than T-Table 2.326 or in other words Hypothesis 1 (H1) was accepted. The result of second hypnotical was 0,689 with T-Statistic 25,687 and more than T-Table 2.326 or in other words Hypothesis 2 (H2) was accepted.
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 Muji Suhartini Siti Chodijah