Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani

Zakat has become one of the vital opportunity to be given to the poor and needy. However, there are problems faced by the institution of zakat with the inefficiency and inaccurate issue, especially in the zakat allocation and distribution aspects. Moreover, the zakat allocation and distribution proc...

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Main Authors: Khairudin, Nurkhairizan, Azlan, Nurul Ain, Azizan, Azilawati, Jelani, Ahmad Bakhtiar
Format: Article
Language:English
Published: UiTM Press 2020
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Institution: Universiti Teknologi Mara
Language: English
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spelling my.uitm.ir.381832023-06-26T04:53:59Z https://ir.uitm.edu.my/id/eprint/38183/ Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani msij Khairudin, Nurkhairizan Azlan, Nurul Ain Azizan, Azilawati Jelani, Ahmad Bakhtiar Malaysia Data processing Online data processing Zakat has become one of the vital opportunity to be given to the poor and needy. However, there are problems faced by the institution of zakat with the inefficiency and inaccurate issue, especially in the zakat allocation and distribution aspects. Moreover, the zakat allocation and distribution process is time consuming due to the variety of the criteria to be considered, especially when it involves an educational institution. Since the problem usually originates from the organization of zakat itself, it is essential to minimize the difficulties so that zakat can be distributed in a proper way to the qualified person with a suitable allocation. Therefore, the purpose of this project is to develop a web-based Zakat Management and Allocation Prediction System using Case-based Reasoning(CBR) technique. The proposed method consists of two components: (1) Web-based zakat management system which aims to properly manage all related data of the zakat applicant, and (2) Zakat allocation module using CBR to suggests the allocation amount of zakat by finding the similarities between the previous cases and the new cases. For the prediction purposes, the significant main features are identified and suitable weightage is assigned to be able the CBR engine to produce a suggestion. Experimental results using real data collected from UiTM(Perak) Tapah Campus show that our proposed model achieves a significant improvement in the efficiency of managing and allocating the amount of zakat. UiTM Press 2020-11 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/38183/2/38183.pdf Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani. (2020) Mathematical Sciences and Informatics Journal (MIJ) <https://ir.uitm.edu.my/view/publication/Mathematical_Sciences_and_Informatics_Journal_=28MIJ=29.html>, 1 (2). pp. 22-33. ISSN 2735-0703 https://mijuitm.com.my/view-articles/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Malaysia
Data processing
Online data processing
spellingShingle Malaysia
Data processing
Online data processing
Khairudin, Nurkhairizan
Azlan, Nurul Ain
Azizan, Azilawati
Jelani, Ahmad Bakhtiar
Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani
description Zakat has become one of the vital opportunity to be given to the poor and needy. However, there are problems faced by the institution of zakat with the inefficiency and inaccurate issue, especially in the zakat allocation and distribution aspects. Moreover, the zakat allocation and distribution process is time consuming due to the variety of the criteria to be considered, especially when it involves an educational institution. Since the problem usually originates from the organization of zakat itself, it is essential to minimize the difficulties so that zakat can be distributed in a proper way to the qualified person with a suitable allocation. Therefore, the purpose of this project is to develop a web-based Zakat Management and Allocation Prediction System using Case-based Reasoning(CBR) technique. The proposed method consists of two components: (1) Web-based zakat management system which aims to properly manage all related data of the zakat applicant, and (2) Zakat allocation module using CBR to suggests the allocation amount of zakat by finding the similarities between the previous cases and the new cases. For the prediction purposes, the significant main features are identified and suitable weightage is assigned to be able the CBR engine to produce a suggestion. Experimental results using real data collected from UiTM(Perak) Tapah Campus show that our proposed model achieves a significant improvement in the efficiency of managing and allocating the amount of zakat.
format Article
author Khairudin, Nurkhairizan
Azlan, Nurul Ain
Azizan, Azilawati
Jelani, Ahmad Bakhtiar
author_facet Khairudin, Nurkhairizan
Azlan, Nurul Ain
Azizan, Azilawati
Jelani, Ahmad Bakhtiar
author_sort Khairudin, Nurkhairizan
title Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani
title_short Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani
title_full Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani
title_fullStr Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani
title_full_unstemmed Zakat management system with allocation prediction using case-based reasoning / Nurkhairizan Khairudin, Nurul Ain Azlan, Azilawati Azizan and Ahmad Bakhtiar Jelani
title_sort zakat management system with allocation prediction using case-based reasoning / nurkhairizan khairudin, nurul ain azlan, azilawati azizan and ahmad bakhtiar jelani
publisher UiTM Press
publishDate 2020
url https://ir.uitm.edu.my/id/eprint/38183/2/38183.pdf
https://ir.uitm.edu.my/id/eprint/38183/
https://mijuitm.com.my/view-articles/
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