Bank customer classification in Indonesia: logistic regression vs artificial neural networks.

Abduh, Muhamad and Dahari, Zainurin and Omar, Mohd. Azmi (2013) Bank customer classification in Indonesia: logistic regression vs artificial neural networks. In: IIUM Research, Invention and Innovation Exhibition 2013, 19 - 20 February 2013, Cultural Activity Centre (CAC) and KAED Gallery, IIUM.

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Abstract

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.

Item Type:	Conference or Workshop Item (Poster)
Subjects:	H Social Sciences > HG Finance > HG1501 Banking
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Institute of Islamic Banking & Finance (IIiBF)
Depositing User:	Dr Muhamad Abduh
Date Deposited:	24 Jul 2013 14:56
Last Modified:	05 Sep 2013 15:18
URI:	http://irep.iium.edu.my/id/eprint/30751

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