ZAKAT APPLICATION TO ESTIMATE ZAKAT REVENUE BY IMPLEMENTING STOCHASTIC DYNAMICAL SYSTEM METHOD - Dwi Asih Haryanti; Feni Andriani; Dewi Putrie Lestari; Beny Susanti; Nurma Nugraha (Media Riset Akuntansi, Auditing & Informasi, 2025)
Zakat is an obligation to spend part of the assets we own in accordance with applicable conditions. In the context of a modern state, zakat plays a significant role in ensuring equitable economic distribution for the welfare of society. In Indonesia, the collection, management, and distribution of zakat are facilitated by the National Zakat Agency (Baznas) at the national level, Regional Zakat Agencies (Bazda) at the local level, and non-governmental Zakat Institutions (Laznas/Lazda). One effort to address poverty issues is through the optimization of zakat implementation, including its distribution and management. This study employs the Stochastic Dynamical System method using the Kalman Filter algorithm to estimate zakat revenue, aiming for optimal distribution and management of zakat. The research involves four stages: Data Analysis and Collection, Application Design, Data Analysis and Collection. Zakat revenue prediction using the Kalman Filter algorithm is conducted by calculating the Mean Absolute Error (MAE), achieving an accuracy rate of 89.6%.