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All Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JTERA (Jurnal Teknologi Rekayasa) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JSI (Jurnal sistem Informasi) Universitas Suryadarma INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika Jurnal Teknik Mesin, Industri, Elektro dan Informatika Gaster JAMU : Jurnal Abdi Masyarakat UMUS Scientica: Jurnal Ilmiah Sains dan Teknologi Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Indrawan Ady Saputro
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Journal : Jurnal Teknik Informatika

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Pengembangan Aplikasi Berbasis Web untuk Pemetaan Penerima Zakat Menggunakan Metode K-Means Clustering Indrawan Ady Saputro; Iwan Ady Prabowo; Riyan Abdul Aziz
JEKIN - Jurnal Teknik Informatika Vol. 4 No. 2 (2024)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jekin.v4i2.721

Abstract

Zakat is an asset collected from muzaki and then distributed to those who are entitled to receive, namely 8 asnaf consisting of very poor people, people who are lacking, zakat management officers, people who have just converted to Islam, people who have a lot of debt, slaves who want to be free, travelers, and those who fight in the way of Allah. In Al-Huda Mosque, the data of zakat recipients currently only displays names, addresses, the number of family dependents, and the amount of zakat distributed. Takmir does not yet know the recipients who are entitled to zakat in large or small amounts. Therefore, an algorithm is required to streamline the grouping of data on zakat recipients in Al-Huda Mosque based on data ratios such as the number of family dependents, work, home conditions, and transportation. This study applies the K-Means Clustering method approach to group zakat recipient data. Web-based applications are developed using PHP to make it easier to manage data and grouping effectively. As a result, 7 recipients received high priority recipients, 30 medium priority recipients, and 16 low priority recipients. Testing of data clusters with the Silhouette Coefficient method showed that 4 clusters have strong structural values. For future research, additional variables can be extracted and analyzed to maximize more accurate and comprehensive grouping results
Co-Authors Abdul Aziz, Riyan Afnan Rosyidi Dwi Setiaji Febrianta Surya Nugraha, Febrianta Surya Ghulam Vicco Febrianta Hadis Turmudi Iwan Ady Prabowo Khaidir Umar Latifah Nurul Habibah Maulina, Rufidah Nugroho Ridho Harjanto Nurhidayanto, Nurhidayanto Pangesti , Oktafian Dyah Prasetiya, Bayu Ade Purwidiantoro, Moch. Hari Rahmadi, Mochammad Luthfi Riyan Abdul Aziz Riyan Abdul Aziz Setiawan Adib Wibowo Siska Ningtyas Prabasari Sugiarto, Lilik Surya Nugraha , Febrianta Suryawati, Liling Daru Susanti, Anggi Tinuk Agustin Wibowo, Alfian Nur Widianti, Ina Sholihah Widiyanti, Sri Yudam, Zaky Zulfahmi