Pemanfaatan Data Mining dalam Penentuan Rekomendasi Mustahik (Penerima Zakat)

  • Andi Abdul malik Ahmad Politeknik Negeri Ujung Pandang
  • Zawiyah Saharuna Politeknik Negeri Ujung Pandang
  • Muhammad Fajri Raharjo Politeknik Negeri Ujung Pandang
Keywords: Data Mining, Artificial Neural Network, Klasifikasi, Zakat


This study applies data mining in determining recommendations for mustahik. The application is carried out using a classification method with an artificial neural network algorithm where the attributes used are age and type of work of the head of the family, the condition and ownership of the residence, the place of sewage, family monthly income, number of dependents, and diet. Tests are carried out using a combination of values ​​between learning rate, epoch, k-fold, and hidden layer neurons. Based on the test results from the classification process, it is found that the artificial neural network algorithm has the highest accuracy when the number of hidden layer neurons is six, the learning rate is one, the fold is seven, and the number of epochs is 200, which is 92.09%. The test results are then displayed on the Mustahik information system page.


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[1] Data dan Informasi Kemiskinan Sulawesi Selatan 2017. Makassar: BPS Provinsi Sulawesi Selatan, 2018.
[2] Data dan Informasi Kemiskinan Sulawesi Selatan 2016. Makassar: BPS Provinsi Sulawesi Selatan, 2017.
[3] Kementerian Agama RI, Panduan Zakat Praktis, vol. 53, no. 9. Kementerian Agama Republik Indonesia, 2013.
[4] A. Fadli, “Konsep Data Minning,” IlmuKomputer.Com, 2011. (accessed Nov. 26, 2018).
[5] H. Annur, “Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes,” Ilk. J. Ilm., vol. 10, no. 2, pp. 160–165, 2018.
[6] A. Wanto, “Penerapan Jaringan Saraf Tiruan Dalam Memprediksi Jumlah Kemiskinan,” Kumpul. J. Ilmu Komput., vol. 05, no. 01, pp. 61–74, 2018.
[7] O. Maimon and L. Rokach, “Introduction to knowledge discovery in database,” Eur. Tel-Aviv - Data Min. Knowl. Discov. Handb., pp. 1–17, 2005.
[8] J. Browniee, “A Gentle Intoduction to k-fold Cross-Validation,” 2018. (accessed Dec. 03, 2020).
How to Cite
Ahmad, A., Saharuna, Z., & Raharjo, M. (2020, December 2). Pemanfaatan Data Mining dalam Penentuan Rekomendasi Mustahik (Penerima Zakat). Elektron : Jurnal Ilmiah, 67-73.