Utilization of Holt's Forecasting Model for Zakat Collection in Indonesia

Abstract

The practice of zakat is gaining popularity in Indonesia. This development is attributed to the strong role of the government in consistently developing zakat infrastructure and the increased awareness of people to practice zakat. Despite this success, a mechanism for predicting future zakat collection has not yet been developed. This study applies Holt's exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) model to forecast zakat in Indonesia using zakat collection from 2009 to 2014. Results show that Holt's exponential smoothing is best fits the zakat time series data and is therefore suitable for forecasting zakat. Holt's exponential smoothing is comparable to the ARIMA model given its small deviations in mean absolute percentage error and mean square error. Moreover, the software used to implement Holt's exponential smoothing is similar to that used in ARIMA models. These similarities show that these models can accurately forecast future trends to prepare proper strategies and plan the future of the organization. These models can also be used to develop a plan for managing charity based on the number of recorded mustahiq.

Utilisation of Holt-Winters Forecasting Model in Lembaga Zakat Selangor (LZS) For Zakat Collection

“…Various studies have shown that ARIMA and Holt Exponential Smoothing (HES) are better predictive models than econometric or other time-series models. [2] used HES and ARIMA models to forecast annual zakat collection in Indonesia from 2009 to 2014. [2] illustrated that HES method fits the time series data of zakat collection in Indonesia very well, thus is suitable to predict future zakat collection.…”

“…[2] used HES and ARIMA models to forecast annual zakat collection in Indonesia from 2009 to 2014. [2] illustrated that HES method fits the time series data of zakat collection in Indonesia very well, thus is suitable to predict future zakat collection. In this study, HES method has smaller error than ARIMA method based on mean absolute percentage error (MAPE) and mean square error (MSE).…”

Measurement of the Zakat Village Index in Curug Depok

“…The position of zakat is mandatory for Muslims (Ahmed, 2004), one of the pillars of Islam (Oktaviani and Bahri, 2018;Rais, 2009), and has a strategic function in improving welfare (Bahri et al, 2019;Kasri, 2016;Ismail et al, 2018), and become an instrument of economists and interest of the community (S, 2016). Even zakat plays an essential role in maintaining social harmony between the rich and the poor (Akbarizan et al, 2016), a means of creating social justice (Sarif and Kamri, 2009), acting as a stabilizer in the economic cycle (Daly and Frikha, 2015).…”

Forecasting Analysis of Zis Collection in Banjar Regency Using Double Exponential Smoothing Method

“…Forecasting method using Double Exponential Smoothing by Holt obtained through an analysis process using two weights in the form of parameter alpha (𝛼) and parameter gamma 𝛾 with a value between 0 to 1 (Makridakis, Wheelwright, & McGee, 1983). This method is used if a time series data has an element of an up or down trend without any seasonal element (Akbarizan, et al, 2016). The following equations are used in the implementation of forecasting using Double Exponential Smoothing: It can be seen that 𝛼 = 0,4 dan 𝛾 = 0,1 it is the right parameter to be used as a smoothing weight for this study with an SSE value of 1,05393 × 10 17 which is the smallest SSE value compared to the SSE value of the parameters 𝛼 and 𝛾 others.…”