Abstract
Predicting the collection of zakat in Malaysian zakat institutions is crucial for effective zakat distribution. The surplus problems in zakat funds motivated this study to use more precise statistical methods to predict the future trend of zakat collection. The main objective of this paper is to forecast monthly zakat collection for 12 months ahead of the Lembaga Zakat Selangor (LZS). This research used the Seasonal Exponential Smoothing (Holt-Winters) model to predict zakat collection in LZS. The study utilised monthly zakat collection time series data from 2010 to 2018. The analysis was carried out using Excel Solver. The findings show that the Holt-Winters model is suitable to forecast the monthly zakat collection of LZS as it accounts for seasonal variation. The finding of this study indicates that the Holt-Winters Multiplicative (HWM) model best fits the monthly zakat collection time series data. The multiplicative form of Holt-Winters model yields 24.51% lower error compared to the additive one using the Mean Absolute Percentage Error (MAPE). The findings of this study will help zakat institutions to accurately predict future zakat collection which may consequently improve the management of zakat distribution without leaving a significant amount of zakat surplus. The forecast results can also be used to create a strategy to handle zakat funds based on the amount of registered asnaf. In addition, the study can serve as a basis for the development of a framework to forecast future zakat collections.
Highlights
According to [17], Prophet Muhammad (PBUH) practiced the idea of al-Fauran whereby the zakat funds raised were promptly distributed. This means that the collected zakat funds were distributed in the interests of the Muslims who were in need at that time as soon as possible
The study found that there are three main factors that lead to zakat surplus which are unmatched amount of zakat collection and zakat distribution, late zakat payment, and difficulty in identifying the eligible zakat recipients. [10] referred to Amil, who was hired and had dispersed all the zakat funds immediately after they were raised, leaving no surplus or balance. It seems that the received zakat funds were and efficiently allocated to the beneficiaries at that time. [24] reported that if the surplus no longer exists in society, the poverty rate will generally decrease and, at the same time, represent a decrease in the crime rate in Malaysia
The results show that Holt-Winters Exponential Smoothing (HWES) is more appropriate than the Auto-Regressive Integrated Moving Average (ARIMA) model based on various accuracy measures such as Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and MAE
Summary
The purpose of this section is to introduce the research topic and key fundamental frameworks that lay the foundation of the study. This section covers the problem statement, research questions, research objectives, the scope of the research as well as the structure of the study
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