Akbarizan, - and Rahmad Kurniawan, - and Mohd Zakree Ahmad Nazri, - and Siti Norul Huda Sheikh Abdullah, - and Sri Murhayati, - and Nurcahaya, - (2018) Using Bayesian Network for Determining The Recipient of Zakat in BAZNAS Pekanbaru. International Conference on Electrical Engineering and Informatics.

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Abstract

Abstract—The National Amil-Zakat Agency (Baznas) in Pekanbaru has the function to collect and distribute zakat in Pekanbaru city. Baznas Pekanbaru should be able to determine Mustahik properly. Mustahik is a person eligible to receive zakat. The Baznas committee interviews and observes every Mustahik candidates to decide whom could be receive the zakat. Current Mustahik determination process could lead to be subjective assessment, due to large number of zakat recipient applicants and the complexity of rules in determining a Mustahik. Therefore, this study utilize artificial intelligence in determining Mustahik. The Bayesian Network method is appropriate to apply as an inference engine. Based on the experimental results, we found that Bayesian network produces a good accuracy 93.24% and effective to use in data set have an uneven class distribution. In addition, based on experiments by setting an alpha estimator’s values, at 0.6 to 1.0 can increase the accuracy of a Bayesian Network to 95.95%. Keywords—bayesian network, baznas pekanbaru, mustahik, zakat

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