Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks

This paper aims to identify factors distinguish Islamic and conventional bank customers in Indonesia. It tries to relate between bank customers’ religiosity, assessment upon certain factors such as bank performance, bank advertisement and main reasons of using banking services towards their decision...

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Main Authors:	Abduh, Muhamad, Dahari, Zainurin, Omar, Mohd. Azmi
Format:	Article
Language:	English
Published:	IDOSI Publication 2012
Subjects:	HA29 Theory and method of social science statistics HG1501 Banking
Online Access:	http://irep.iium.edu.my/25482/ http://irep.iium.edu.my/25482/ http://irep.iium.edu.my/25482/ http://irep.iium.edu.my/25482/1/Bank_Customer_Classification_in_Indonesia.pdf

id	iium-25482
recordtype	eprints
spelling	iium-254822012-08-09T06:04:22Z http://irep.iium.edu.my/25482/ Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks Abduh, Muhamad Dahari, Zainurin Omar, Mohd. Azmi HA29 Theory and method of social science statistics HG1501 Banking This paper aims to identify factors distinguish Islamic and conventional bank customers in Indonesia. It tries to relate between bank customers’ religiosity, assessment upon certain factors such as bank performance, bank advertisement and main reasons of using banking services towards their decision on which bank they had joined. Logistic regression and neural networks models are used to answer the research questions based on 520 customers reside in Jakarta. Data collection is done through a direct survey using self administered questionnaire. The results from logistic regression and neural networks models demonstrate that shariah compliant issues, customers’ awareness on the fatwa announced by National Ulama Council on the impermissibility of bank interest, safety of fund as main reason of using banking services and customers’perception on bank advertisement are the significant factors which classify the bank customers in Indonesia. Nonetheless, neural network classifies better than logistic regression. IDOSI Publication 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/25482/1/Bank_Customer_Classification_in_Indonesia.pdf Abduh, Muhamad and Dahari, Zainurin and Omar, Mohd. Azmi (2012) Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks. World Applied Sciences Journal , 18 (7). pp. 933-938. ISSN 1818-4952 http://idosi.org/wasj/wasj18(7)12/12.pdf 10.5829/idosi.wasj.2012.18.07.1226
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	HA29 Theory and method of social science statistics HG1501 Banking
spellingShingle	HA29 Theory and method of social science statistics HG1501 Banking Abduh, Muhamad Dahari, Zainurin Omar, Mohd. Azmi Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks
description	This paper aims to identify factors distinguish Islamic and conventional bank customers in Indonesia. It tries to relate between bank customers’ religiosity, assessment upon certain factors such as bank performance, bank advertisement and main reasons of using banking services towards their decision on which bank they had joined. Logistic regression and neural networks models are used to answer the research questions based on 520 customers reside in Jakarta. Data collection is done through a direct survey using self administered questionnaire. The results from logistic regression and neural networks models demonstrate that shariah compliant issues, customers’ awareness on the fatwa announced by National Ulama Council on the impermissibility of bank interest, safety of fund as main reason of using banking services and customers’perception on bank advertisement are the significant factors which classify the bank customers in Indonesia. Nonetheless, neural network classifies better than logistic regression.
format	Article
author	Abduh, Muhamad Dahari, Zainurin Omar, Mohd. Azmi
author_facet	Abduh, Muhamad Dahari, Zainurin Omar, Mohd. Azmi
author_sort	Abduh, Muhamad
title	Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks
title_short	Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks
title_full	Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks
title_fullStr	Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks
title_full_unstemmed	Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks
title_sort	bank customer classification in indonesia: logistic regression vis-a-vis artificial neural networks
publisher	IDOSI Publication
publishDate	2012
url	http://irep.iium.edu.my/25482/ http://irep.iium.edu.my/25482/ http://irep.iium.edu.my/25482/ http://irep.iium.edu.my/25482/1/Bank_Customer_Classification_in_Indonesia.pdf
first_indexed	2023-09-18T20:37:58Z
last_indexed	2023-09-18T20:37:58Z
_version_	1777409172990590976

Bank customer classification in Indonesia: logistic regression vis-a-vis artificial neural networks

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