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Artificial Neural Network with Backpropogation Method in Predicting Sukuk Retail State Based on Age Categories in Promoting Economic Growth


Dedi Suhendro, S.E., M.Si, (2018) Artificial Neural Network with Backpropogation Method in Predicting Sukuk Retail State Based on Age Categories in Promoting Economic Growth, Prosiding ,Universitas Simalungun
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Dedi Suhendro, S.E., M.Si, | pdf
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Abstrak
Sukuk Retail State has fixed remuneration that paid every month. The government gains equity from the use
of public funds, while the public gets a profit from the investment. The contribution of this research
provides benefits for promoting optimally on the next sukuk issuance. Referral data sourced from Ministry
of Finance through website www.djppr.kemenkeu.go.id. The data are sukuk sales data series 003 - 009
which are grouped into several categories namely geography, profession and age category. The method used
is Artificial Neural Network Backpropogation. The input variables used are age category <25 (X1), age
category 25 - 40 (X2), age category 41 - 55 (X3), and age category> 55 (X4) with model of training
architecture and test of 4 architecture ie 4-2-1, 4-5-1, 4-2-5-1 and 4-5-2-1. The results of this study provide
the best architecture 4-2-1 with epoch 1593, MSE 0.00099950214 and 71% accuracy rate. Furthermore, the
sensitivity analysis was performed to determine the best performing variables, resulting in the 41-55 (X3)
age category variable with a score of 0.4089. Thus obtained the prediction of most investors on the purchase
of sukuk series 010 is the age category 41 - 55.