KHAIRUL AMRI, - and Rado Yendra, - and Muhammad Marizal, - and Ari Pani Desvina, - and RAHMADENI, - The Comparison of Exponential Regression and Exponential Smoothing Holt Winter 2 Variable in Zakat Modelling.

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Abstract

Zakat is an important worship for Muslims, where some of the wealth of the rich will be distributed to the poor according to certain rules. Zakat can be used as a source of income for a country, such as Indonesia with a majority Muslim population. This study focuses on modeling zakat in Indonesia using zakat data from 2004 to 2019. The zakat data obtained continues to increase exponentially, therefore the main goal of this study is to find the best model to the zakat data. For this purpose two statistical models, namely the exponential regression model and the exponential smoothing 2 variables will be used and tested to determine the best model to describe zakat in Indonesia. The best model will be selected based on graphical inspection and, numerical criteria namely Mean Absolut Error (MAE) and Mean Square Error (MSE). In most the cases, graphical inspection gave the same result but their MAE and MSE result differed. The best model was chosen as the model with the lowest values of MAE and MSE. In general, the Exponential Smoothing 2 Variables has been selected as the best model. Keywords - Exponential Regression, Exponential Smoothing 2 Variables, MAE, MSE, Zakat Model.

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