FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA

The aim of this paper is to test the ability of artificial neural network (ANN) as an alternative method in time series forecasting and compared to autoregressive integrated moving average (ARIMA) in studying saving deposit in Malaysian Islamic banks. Artificial neural network is getting popular a...

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Autores principales:	Raditya Sukmana, Mahmud Iwan Solihin
Formato:	article
Lenguaje:	EN
Publicado:	Universitas Muhammadiyah Yogyakarta 2014
Materias:	artificial neural network arima saving deposit Economic theory. Demography HB1-3840
Acceso en línea:	https://doaj.org/article/b408d634a0ba4e598e095321b0ecc9da
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spelling	oai:doaj.org-article:b408d634a0ba4e598e095321b0ecc9da2021-12-02T13:13:54ZFORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA1411-99002541-5506https://doaj.org/article/b408d634a0ba4e598e095321b0ecc9da2014-10-01T00:00:00Zhttps://journal.umy.ac.id/index.php/esp/article/view/1517https://doaj.org/toc/1411-9900https://doaj.org/toc/2541-5506The aim of this paper is to test the ability of artificial neural network (ANN) as an alternative method in time series forecasting and compared to autoregressive integrated moving average (ARIMA) in studying saving deposit in Malaysian Islamic banks. Artificial neural network is getting popular as an alternative method in time series forecasting for its capability to capture volatility pattern of non-linear time series data. In addition, the use of an established tool of analysis such as ARIMA is of importance here for comparative purposes. These two methods are applied to monthly data of the Malaysian Islamic banking deposits from January 1994 to November 2005. The result provides evidence that ANN using “early stopping” approach can be used as an alternative forecasting engine with univariate time series model. It can predict non-linear time series using the pattern of the data directly without any statistical analysis.Raditya SukmanaMahmud Iwan SolihinUniversitas Muhammadiyah Yogyakartaarticleartificial neural networkarimasaving depositEconomic theory. DemographyHB1-3840ENJurnal Ekonomi & Studi Pembangunan, Vol 8, Iss 2, Pp 154-161 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial neural network arima saving deposit Economic theory. Demography HB1-3840
spellingShingle	artificial neural network arima saving deposit Economic theory. Demography HB1-3840 Raditya Sukmana Mahmud Iwan Solihin FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA
description	The aim of this paper is to test the ability of artificial neural network (ANN) as an alternative method in time series forecasting and compared to autoregressive integrated moving average (ARIMA) in studying saving deposit in Malaysian Islamic banks. Artificial neural network is getting popular as an alternative method in time series forecasting for its capability to capture volatility pattern of non-linear time series data. In addition, the use of an established tool of analysis such as ARIMA is of importance here for comparative purposes. These two methods are applied to monthly data of the Malaysian Islamic banking deposits from January 1994 to November 2005. The result provides evidence that ANN using “early stopping” approach can be used as an alternative forecasting engine with univariate time series model. It can predict non-linear time series using the pattern of the data directly without any statistical analysis.
format	article
author	Raditya Sukmana Mahmud Iwan Solihin
author_facet	Raditya Sukmana Mahmud Iwan Solihin
author_sort	Raditya Sukmana
title	FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA
title_short	FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA
title_full	FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA
title_fullStr	FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA
title_full_unstemmed	FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA
title_sort	forecasting saving deposit in malaysian islamic banking: comparison between artificial neural network and arima
publisher	Universitas Muhammadiyah Yogyakarta
publishDate	2014
url	https://doaj.org/article/b408d634a0ba4e598e095321b0ecc9da
work_keys_str_mv	AT radityasukmana forecastingsavingdepositinmalaysianislamicbankingcomparisonbetweenartificialneuralnetworkandarima AT mahmudiwansolihin forecastingsavingdepositinmalaysianislamicbankingcomparisonbetweenartificialneuralnetworkandarima
_version_	1718393407970213888

FORECASTING SAVING DEPOSIT IN MALAYSIAN ISLAMIC BANKING: COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORK AND ARIMA

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