Factors Affecting the Eligibility of Zakat Assistance to University Students during COVID-19: A case study in Universiti Teknologi MARA (UiTM)

Azlan Abdul Aziz; Nor Azriani Mohamad Nor; Wan Nurshazelin Wan Shahidan; Siti Nor Nadrah Mohamad

doi:10.21834/e-bpj.v8iSI14.5059

Authors

Azlan Abdul Aziz Kolej Pengajian Pengkomputeran, Informatik dan Media, Universiti Teknologi MARA Cawangan Perlis, Perlis; Malaysia Statistical Analytics, Forecasting & Innovation (SAFI) Research Interest Group, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia
Nor Azriani Mohamad Nor Kolej Pengajian Pengkomputeran, Informatik dan Media, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia; Statistical Analytics, Forecasting & Innovation (SAFI) Research Interest Group, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia
Wan Nurshazelin Wan Shahidan Kolej Pengajian Pengkomputeran, Informatik dan Media, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia; Statistical Analytics, Forecasting & Innovation (SAFI) Research Interest Group, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia
Siti Nor Nadrah Mohamad Kolej Pengajian Pengkomputeran, Informatik dan Media, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia; Statistical Analytics, Forecasting & Innovation (SAFI) Research Interest Group, Universiti Teknologi MARA Cawangan Perlis, Perlis, Malaysia

DOI:

https://doi.org/10.21834/e-bpj.v8iSI14.5059

Keywords:

Zakat, COVID-19, Binary Logistic Regression, ZAWAF

Abstract

The Unit Zakat, Sedekah & Wakaf (ZAWAF) Universiti Teknologi MARA (UiTM) Cawangan Perlis has offered Islamic financial assistance such as Zakat Sara Diri, Zakat Yuran Pengajian, and Zakat Komputer Riba to students during online pandemic COVID-19. Therefore, ZAWAF needs to identify factors contributing to the eligibility for Zakat assistance. The Binary Logistic regression model was used to determine the significant factors. Stepwise selection procedures are used to yield the most appropriate regression equation. Wald statistics were used to determine the significant factors. Four factors significantly are the Head of a family's monthly income, mother's monthly income, family dependents, and gender.

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