C4.5 Decision Tree Implementation in Sistem Informasi Zakat (Sizakat) to Automatically Determining the Amount of Zakat Received by Mustahik

Abstract

In general, Zakat Information Systems is established to manage the zakat services, so that the data can be well documented. This study proposes the existence of a feature that will determine the amount of zakat received by Mustahik automatically using C4.5 Decision Tree algorithm. This feature is expected to make the process of determining the amount of zakat be done easy and optimal. The data used in this study are the data taken from Masjid An-Nur, Pancoran, South Jakarta. The experiment results show that the proposed feature produces an accuracy rate over 85%. Keywords: C4.5 algorithm, classification, data mining, decision tree, SiZakat AbstrakPada umumnya Sistem Informasi Zakat dibangun untuk mengelola pelayanan zakat, sehingga data dapat terdokumentasi secara baik. Penelitian ini mengajukan adanya suatu fitur penentuan jumlah zakat yang akan diterima Mustahik secara otomatis dengan memanfaatkan algoritma C4.5 Decision Tree. Dengan adanya fitur tersebut diharapkan proses penentuan jumlah zakat dapat dilakukan secara mudah dan optimal. Data yang digunakan dalam penelitian ini merupakan data yang diambil dari Masjid AnNur Pancoran Jakarta Selatan. Hasil dari eksperimen yang dilakukan menunjukkan fitur yang diajukan menghasilkan tingkat akurasi lebih dari 85%.

Credit Classification Using CRISP-DM Method On Bank ABC Customers

“…C4.5 algorithm is an algorithm developed by J. Ross Quinlan in 1993 [8]. The C4.5 algorithm is a continued development of the previous algorithm, namely the ID3 algorithm.…”

“…Therefore, the actual ID3 and C4.5 algorithms have the same basic principles. Some developments are done on the algorithm C4.5 algorithm that makes the C4.5 different from its predecessor, that is [8] :…”

“… Ability to handle attributes with discrete or continuous type [8]  Ability to handle empty attribute (missing value) [8].  Can do pruning on branches [8].…”

“… Ability to handle attributes with discrete or continuous type [8]  Ability to handle empty attribute (missing value) [8].  Can do pruning on branches [8].  The selection is done using a calculation attribute Gain Ratio [8] Here are the three principles of the work done by the C4.5 algorithm according to [8] :  First, perform decision tree construction.…”

“… Can do pruning on branches [8].  The selection is done using a calculation attribute Gain Ratio [8] Here are the three principles of the work done by the C4.5 algorithm according to [8] :  First, perform decision tree construction. The purpose of this decision tree construction algorithm is to create a model of a set of training data that will be used to predict the class of a new data [8]  Second, the decision tree pruning.…”