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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| Language: | en |
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UiTM Press
2020
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| Online Access: | 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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| _version_ | 1863791175417200640 |
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| 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 |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.uitm.ir-38183 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 2020 |
| publisher | UiTM Press |
| record_format | eprints |
| spelling | my.uitm.ir-381832026-04-22T07:39:15Z 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 Khairudin, Nurkhairizan and Azlan, Nurul Ain and Azizan, Azilawati and Jelani, Ahmad Bakhtiar (2020) 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/ 10.24191/mij.v1i2.10931 10.24191/mij.v1i2.10931 10.24191/mij.v1i2.10931 |
| 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 |
| title | 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_short | 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 |
| topic | Malaysia Data processing Online data processing |
| 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/ |
| url_provider | http://ir.uitm.edu.my/ |