Predicting Future Depositor`s Rate of Return Applying Neural Network: A Case-study of Indonesian Islamic Bank | Zendy

Saiful Anwar | Zendy; Kenji Watanabe | Zendy

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Predicting Future Depositor`s Rate of Return Applying Neural Network: A Case-study of Indonesian Islamic Bank

Author(s) -

Saiful Anwar,

Kenji Watanabe

Publication year - 2010

Publication title -

international journal of economics and finance

Language(s) - English

Resource type - Journals

eISSN - 1916-9728

pISSN - 1916-971X

DOI - 10.5539/ijef.v2n3p170

Subject(s) - exchange rate , circulation (fluid dynamics) , econometrics , artificial neural network , certificate , inflation (cosmology) , indonesian , interest rate , currency , computer science , economics , finance , monetary economics , artificial intelligence , algorithm , engineering , linguistics , philosophy , physics , theoretical physics , aerospace engineering

Islamic bank has to perform well in order to deliver better return in compensating depositor`s money. This paper is conducted to identify the relative significance assigned to macroeconomics variables for maximizing depositor’s opportunity. Furthermore, it becomes very necessary to have a prediction of future rate of return to get a clear picture in making deposit decision. This research uses some key macroeconomic variables such as; Jakarta Stock Indices (JSI), inflation rate (INFR), central bank`s interest rate certificate (INTR), exchange rate (ER), and money in circulation (MIC). Since these variables are characterized as nonlinearities time series data, Artificial Neural Networks (ANN) is employed using back propagation algorithm as learning algorithm. From observation resulted that central bank’s interest rate certificate (INTR) and Money In Circulation (MIC) could be used as leading indicators to face the problem with 94.95% accuracy.

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