K-Means Clustering Algorithm for Grouping Eligible Community Recipients of Government Assistance

Authors

  • Farid Helmy Muzaqqi Universitas Amikom Purwokerto, Purwokerto
  • Desty Rakhmawati Universitas Amikom Purwokerto, Purwokerto
  • Anugerah Bagus Wijaya Universitas Amikom Purwokerto, Purwokerto

DOI:

https://doi.org/10.30865/mib.v8i3.7766

Keywords:

Clustering, K-Means Algorithm, Data Mining, Recipients, Government Assistance

Abstract

The government assistance program is financial support provided to the community with the aim of helping to improve the quality of life and welfare of almost all provinces in Indonesia including Central Java Province, especially in Ajibarang District, Banyumas Regency. This program aims to overcome the gap between the upper middle economic community and the lower middle economic community. However, the implementation of aid so far has not been even and fair, so it has not achieved its goal of helping people who really need it. In the process of providing assistance, it is important to have a strong basic foundation in determination and decision making. The program must ensure that aid is provided to truly deserving communities. The problem is that aid programs often do not work as intended, and are not effective in addressing economic inequality. One way to resolve this issue is to review the recipient's previous data. This research uses data mining to extract data from people who deserve assistance or not by applying clustering methods. Clustering, which is the process of grouping data without a class target (unsupervised learning), was used in this study. The algorithm used in this research is K-Means clustering. The results showed that there were two clusters of K-Means algorithm application, with 6 people in cluster 1 and 4 people in cluster 2. This research was successful and had an impact on aid providers to conduct more thorough data collection not just choosing the community to be given assistance.

References

N. Hendrastuty, “Penerapan Data Mining Menggunakan Algoritma K-Means Clustering Dalam Evaluasi Hasil Pembelajaran Siswa,†2024, Doi: 10.58602/Jima-Ilkom.V3i1.26.

S. Natalia Br Sembiring, H. Winata, S. Kusnasari, S. Informasi, And S. Triguna Dharma, “Pengelompokan Prestasi Siswa Menggunakan Algoritma K-Means,†2023.

M. Qori’atunnadyah, “Pengelompokkan Wilayah Berdasarkan Rasio Guru-Murid Pada Jenjang Pendidikan Menggunakan Algoritma K-Means,†2022.

T. Hartati, O. Nurdiawan, E. Wiyandi, And S. I. Cirebon, “Analisis Dan Penerapan Algoritma K-Means Dalam Strategi Promosi Kampus Akademi Maritim Suaka Bahari,†2021.

T. Hardiani, “Analisis Clustering Kasus Covid 19 Di Indonesia Menggunakan Algoritma K-Means,†Jurnal Nasional Pendidikan Teknik Informatika (Janapati), Vol. 11, No. 2, Pp. 156–165, Aug. 2022, Doi: 10.23887/Janapati.V11i2.45376.

M. Sholeh And K. Aeni, “String (Satuan Tulisan Riset Dan Inovasi Teknologi) Perbandingan Evaluasi Metode Davies Bouldin, Elbow Dan Silhouette Pada Model Clustering Dengan Menggunakan Algoritma K Means,†2021.

N. Luh, P. P. Dewi, I. Nyoman Purnama, And N. W. Utami, “Penerapan Data Mining Untuk Clustering Penilaian Kinerja Dosen Menggunakan Algoritma K-Means (Studi Kasus: Stmik Primakara),†Jurnal Ilmiah Teknologi Informasi Asia, Vol. 16, No. 2, 2022.

M. Djaka Permana, A. Lia Hananto, E. Novalia, B. Huda, And T. Paryono, “Klasterisasi Data Jamaah Umrah Pada Tanurmutmainah Tour Menggunakan Algoritma K-Means,†Jurnal Komtekinfo, Pp. 15–20, Feb. 2023, Doi: 10.35134/Komtekinfo.V10i1.332.

H. Syahputra, “Clustering Tingkat Penjualan Menu (Food And Beverage) Menggunakan Algoritma K-Means,†Jurnal Komtekinfo, Pp. 29–33, Mar. 2022, Doi: 10.35134/Komtekinfo.V9i1.274.

Z. I. Alfianti, “Pengelompokan Wilayah Penyebaran Covid-19 Di Kabupaten Karawang Menggunakan Algoritma K-Means,†Jurnal Ilmiah Informatika Komputer, Vol. 26, No. 2, Pp. 111–122, 2021, Doi: 10.35760/Ik.2021.V26i2.4155.

R. Gustrianda And D. I. Mulyana, “Penerapan Data Mining Dalam Pemilihan Produk Unggulan Dengan Metode Algoritma K-Means Dan K-Medoids,†Jurnal Media Informatika Budidarma, Vol. 6, No. 1, P. 27, Jan. 2022, Doi: 10.30865/Mib.V6i1.3294.

E. Mayoana Fitri, R. Randy Suryono, And A. Wantoro, “Klasterisasi Data Penjualan Berdasarkan Wilayah Menggunakan Metode K-Means Pada Pt Xyz,†2023.

I. Nyoman And M. Adiputra, “Clustering Penyakit Dbd Pada Rumah Sakit Dharma Kerti Menggunakan Algoritma K-Means,†Insert: Information System And Emerging Technology Journal, Vol. 2, No. 2, P. 99, 2021.

R. N. Fahmi, M. Jajuli, N. Sulistiyowati, And U. S. Karawang, “Analisis Pemetaan Tingkat Kriminalitas Di Kabupaten Karawang Menggunakan Algoritma K-Means Mapping Analysis Of Criminality Level In Karawang Using K-Means Algorithm,†Journal Of Information Technology And Computer Science (Intecoms), Vol. 4, No. 1, 2021, [Online]. Available: Www.Pasundanekspres.Co

M. R. Muttaqin And M. Defriani, “Algoritma K-Means Untuk Pengelompokan Topik Skripsi Mahasiswa,†Ilkom Jurnal Ilmiah, Vol. 12, No. 2, Pp. 121–129, Aug. 2020, Doi: 10.33096/Ilkom.V12i2.542.121-129.

A. Sulistiyawati And E. Supriyanto, “Implementasi Algoritma K-Means Clustring Dalam Penetuan Siswa Kelas Unggulan,†Vol. 15, No. 2. 2022.

A. Amrullah Et Al., “Analisis Cluster Faktor Penunjang Pendidikan Menggunakan Algoritma K-Means (Studi Kasus: Kabupaten Karawang),†2022. [Online]. Available: Http://E-Journal.Stmiklombok.Ac.Id/Index.Php/Jirehttp://E-Journal.Stmiklombok.Ac.Id/Index.Php/Jire

S. Regina, E. Sutinah, And N. Agustina, “Clustering Kualitas Kinerja Karyawan Pada Perusahaan Bahan Kimia Menggunakan Algoritma K-Means,†Jurnal Media Informatika Budidarma, Vol. 5, No. 2, P. 573, Apr. 2021, Doi: 10.30865/Mib.V5i2.2909.

A. Fadilah, M. Nurfaizy P, S. Lumbanbatu, And S. Defiyanti, “Pengelompokan Kabupaten/Kota Di Indonesia Berdasarkan Faktor Penyebab Stunting Pada Balita Menggunakan Algoritma K-Means,†Jurnal Informatika Dan Komputer), Vol. 6, No. 2, Pp. 223–230, 2022.

A. Pangestu And D. T. Ridwan, “Penerapan Data Mining Menggunakan Algoritma K-Means Pengelompokan Pelanggan Berdasarkan Kubikasi Air Terjual Menggunakan Weka,†2021. [Online]. Available: Https://Jurnal.Umj.Ac.Id/Index.Php/Just-It/Index

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Published

2024-07-26

Issue

Vol. 8 No. 3 (2024): Juli 2024

Section

Articles

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