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2022 5th International Conference of Computer and Informatics Engineering (IC2IE)最新文献

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A Web-Based Zakat Recipient Determination System using the Naïve Bayes Algorithm 使用Naïve贝叶斯算法的基于web的天课接收者确定系统
Pub Date : 2022-09-13 DOI: 10.1109/IC2IE56416.2022.9970014
R. Kurniawan, Nurkholis, Mohd Zakree Ahmad Nazri, F. Lestari, R. Salambue, Sukamto
As the third pillar of Islam, zakat must be fulfilled by Muslims who have met the requirements of Islamic law. In Indonesia, zakat is managed by by the National Amil Zakat Agency (BAZNAS). BAZNAS is obliged to distribute zakat to eligible people who call in Islamic is Mustahiq to receive zakat according to the applicable category rules. Mustahiq (beneficiaries) are groups entitled to receive zakat according to the priority scale arranged in the Zakat program. As a case study, BAZNAS in Pekanbaru city determines the recipient of zakat manually by interviewing each candidate. Factors influencing decisions, such as feelings, emotions, sentiments, and moods, can lead to wrong decisions. Human weakness contrasts with the advantages of artificial intelligence. Therefore, this study aimed to design and build a web-based application system to determine the category of the recipient of zakat automatically and quickly using the Naïve Bayes algorithm. A total of 3222 data in 2015–2017 were obtained in BAZNAS Pekanbaru for training data. Based on the experimental testing results, the highest accuracy was 93.7%, and F-measure was 96.7% in 80% of training data. Based on the test results, it can be concluded that web-based applications using the Naïve Bayes method has the potential to be used in determining the recipient of zakat in BAZNAS Pekanbaru.
天课作为伊斯兰教的第三大支柱,必须由符合伊斯兰教法要求的穆斯林来履行。在印度尼西亚,天课由国家天课机构(BAZNAS)管理。BAZNAS有义务根据适用的类别规则,将天课分发给符合条件的人,这些人在伊斯兰教的Mustahiq中呼吁接受天课。Mustahiq(受益人)是根据天课计划安排的优先等级有权接受天课的群体。作为一个案例研究,北干巴鲁市的BAZNAS通过面试每个候选人来手动确定天课的接受者。影响决策的因素,如感觉、情绪、情绪和情绪,都可能导致错误的决策。人类的弱点与人工智能的优势形成鲜明对比。因此,本研究旨在设计并构建一个基于web的应用系统,利用Naïve贝叶斯算法自动快速地确定天课接受者的类别。2015-2017年在BAZNAS Pekanbaru共获得3222个数据作为培训数据。根据实验测试结果,在80%的训练数据中,最高准确率为93.7%,F-measure为96.7%。根据测试结果,可以得出结论,使用Naïve贝叶斯方法的基于web的应用程序有可能用于确定BAZNAS Pekanbaru天课的接收者。
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引用次数: 2
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2022 5th International Conference of Computer and Informatics Engineering (IC2IE)
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