Penerapan Data Mining Dalam Menentukan Kelayakan Penerima Bantuan Sosial Pemko Dengan Algoritma C4.5 (Kasus Kantor Kelurahan Martoba)

Winda Lidysari(1*), Heru Satria Tambunan(2), Hendry Qurniawan(3),

(1) STIKOM Tunas Bangsa, Pematangsiantar
(2) STIKOM Tunas Bangsa, Pematangsiantar
(3) STIKOM Tunas Bangsa, Pematangsiantar
(*) Corresponding Author

Abstract


Social assistance, commonly known as Bansos, is a government program charged by the Regional Revenue and Expenditure Budget. According to the general provisions of article 15 of the Ministerial Regulation Number 32 of 2011 concerning the Provision of Subsidies and Social Assistance in the Regional Revenue and Expenditure Budget, the definition of social assistance applies to the provision of individuals, families, community groups that are unsustainable and selective in nature to prevent possible social risks. The Pematangsiantar City Government provides various kinds of assistance programs, one of which is the PEMKO Social Assistance which is distributed by the Martoba Village Office. In the selection process to determine the recipients of PEMKO Social Assistance at the Martoba Village Office, they still have not fully used information technology to support employee performance. So there are obstacles and it takes a long time. Therefore, we need a system that can help employees more easily determine beneficiaries. Application of Data Mining is a series of processes to find added value semi-manually in the form of unknown knowledge from a data set. In this study, it has parameters, namely, the number of dependents, work, income and home status. By applying the Data Mining Algorithm C4.5, it is hoped that it will make it easier and faster for employees to determine the recipients of PEMKO Social Assistance at the Martoba Village Office

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References


N. Fajira, “Analisis Kepuasan Pelanggan Terhadap Kualitas Pelayanan Pada Kentucky Fried Chicken Cabang Palembang Square Mall,” Polsri, pp. 14–20, 2014.

A. D. I. Suradi, “Penerapan data mining untuk menentukan rekomendasi beasiswa dengan metode algoritma c4.5,” 2018.

T. R. I. B. Tusarwenda, “Penerapan data mining dengan algoritma c4.5 dalam prediksi penjualan botol pada CV. seribukilo,” 2018.

Hendrianto, “Manajemen Strategi Pengelolaan Pasar Dalam Meningkatkan Pendapatan Pedagang Perspektif Ekonomi Islam (Studi di Pasar Segamas Purbalingga),” pp. 1–94, 2018.

L. N. Rani, “Klasifikasi Nasabah Menggunakan Algoritma,” J. KomTekInfo Fak. Ilmu Komput., vol. 2, no. 2, pp. 33–38, 2015.

D. K. Widiyati, M. Wati, and H. S. Pakpahan, “Penerapan Algoritma ID3 Decision Tree Pada Penentuan Penerima Program Bantuan Pemerintah Daerah di Kabupaten Kutai Kartanegara,” J. Rekayasa Teknol. Inf., vol. 2, no. 2, p. 125, 2018, doi: 10.30872/jurti.v2i2.1864.

P. Alkhairi, I. S. Damanik, and A. P. Windarto, “Penerapan Jaringan Saraf Tiruan untuk Mengukur Korelasi Beban Kerja Dosen Terhadap Peningkatan Jumlah Publikasi,” Pros. Semin. Nas. Ris. Inf. Sci., vol. 1, no. September, p. 581, 2019, doi: 10.30645/senaris.v1i0.65.

L. Swastina, “Penerapan Algoritma C4.5 untuk Penentuan Jurusan Mahasiswa,” J. Gema Aktual., vol. 2, no. 1, pp. 93–98, 2013.

A. H. Nasrullah, “Penerapan Metode C4.5 untuk Klasifikasi Mahasiswa Berpotensi Drop Out,” Ilk. J. Ilm., vol. 10, no. 2, p. 244, 2018, doi: 10.33096/ilkom.v10i2.300.244-250.

Y. S. Luvia, A. P. Windarto, S. Solikhun, and D. Hartama, “Penerapan Algoritma C4.5 Untuk Klasifikasi Predikat Keberhasilan Mahasiswa Di Amik Tunas Bangsa,” Jurasik (Jurnal Ris. Sist. Inf. dan Tek. Inform., vol. 1, no. 1, p. 75, 2017, doi: 10.30645/jurasik.v1i1.12.

S. Haryati, A. Sudarsono, and E. Suryana, “Implementasi Data Mining Untuk Memprediksi Masa Studi Mahasiswa Menggunakan Algoritma C4.5 (Studi Kasus: Universitas Dehasen Bengkulu),” J. Media Infotama, vol. 11, no. 2, pp. 130–138, 2015.

A. P. W. Putrama Alkhairi, “Penerapan K-Means Cluster Pada Daerah Potensi Pertanian Karet Produktif di Sumatera Utara.” 2019.

W. A. Triyanto, “Algoritma K-Medoids Untuk Penentuan Strategi Pemasaran Produk,” J. SIMETRIS, vol. 6, no. 1, pp. 183–188, 2015.




DOI: https://doi.org/10.30645/kesatria.v3i1.97

DOI (PDF): https://doi.org/10.30645/kesatria.v3i1.97.g97

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