Implementation of Data Mining in Grouping Data of the Poor Using the K-Means Method
DOI:
10.47709/cnahpc.v5i2.2625Keywords:
Data mining, K-Means, The poorDimension Badge Record
Abstract
Processed, especially data on people who are classified as poor. So that the provision of assistance from the central government or donors is right on target. In village governance, data processing often occurs that is not good and does not use technology, so if any assistance is provided it will make it difficult for the village government to distribute it to poor people. This study aims to classify the data of the poor by implementing data mining and applying the K-means algorithm for grouping data of the poor by applying the K-means algorithm. The research method used is observation research methods and direct interviews to obtain problems and data needed in data processing. The data used is community data. The results of the study obtained that the poor community group was divided into three parts, namely: Poor, Simple, and Able. So it can be seen that there is no shift or change in the data group towards the center of the cluster.
Downloads
Abstract viewed = 123 times
References
Arifullah, M., Hardinata, J. T., & Purba, Y. P. (2022). Implementasi Metode K-Means Dalam Klasifikasi Desa / Kelurahan Menurut Jenis Industri Kecil Mikro. 2(1), 35–42.
Ganda, L., Putra, R., & Anggrawan, A. (2021). Pengelompokan Penerima Bantuan Sosial Masyarakat dengan Metode Grouping of Recipients of Community Social Assistance with the K-Means Method. 21(1), 205–214. https://doi.org/10.30812/matrik.v21i1.1554
Indraputra, R. A., & Fitriana, R. (2020). K-Means Clustering Data COVID-19. 10(3), 275–282.
Kasim, R. J., Bahri, S., & Amir, S. (2012). Implementasi Metode K-Means Untuk Clustering Data Penduduk Miskin Dengan Systematic Random Sampling. 95–101.
Khairi, A. (2021). Implementasi K-Nearest Neighbor (KNN) untuk Klasifikasi Masyarakat Pra Sejahtera Desa Sapikerap Kecamatan Sukarapu. Jurnal TRILOGI, 2(3), 319–323. https://ejournal.unuja.ac.id/index.php/trilogi/article/view/2878
Kristyawan, Y., Sumirat, L. P., Informatika, J., & Teknik, F. (2019). ANALISIS TERHADAP FAKTOR-FAKTOR YANG. 12(2), 95–102.
Kurnia, F., Kom, S., Kurniawan, J., & St, I. F. (2019). Klasifikasi Keluarga Miskin Menggunakan Metode K- Nearest Neighbor Berbasis Euclidean Distance. November, 230–239.
Nurmayanti, W. P., Ayu, D., Saky, L., Malthuf, M., Gazali, M., & Hirzi, R. H. (2021). “ Klasifikasi Home Layak Huni di Kabupaten Brebes dengan Menggunakan Metode Learning Vector. 5(September 2019), 123–132. https://doi.org/10.29408/geodika.v5i1.3430
Premana, A., & Wijaya, A. P. (2022). Klasifikasi Jenis Buah Mangga Menggunakan Metode K-Means Clustering. 5(November), 2–7.
Raharja, M. A., & Supriana, I. W. (n.d.). ANALISIS KLASIFIKASI TINGGKAT KESEHATAN LEMBAGA PERKREDITAN DESA ( LPD ) MENGGUNAKAN METODE K-MEANS CLUSTERING. 83–90.
Rustam, S., & Annur, H. (2019). AKADEMIK DATA MINING ( ADM ) K-MEANS DAN K-MEANS K-NN UNTUK MENGELOMPOKAN KELAS MATA KULIAH KOSENTRASI. 11(28), 260–268.
Sinaga, B., Manurung, J., Mayana, N., Tarigan, B., Feronika, S., & Sitepu, B. (2022). Application of with C4 . 5 algorithm to measure the level of student satisfaction with student services. 7(3), 2134–2143.
Sudibyo, N. A., Iswardani, A., Sari, K., Suprihatiningsih, S., Duta, U., Surakarta, B., & Padjadjaran, U. (2020). PENERAPAN DATA MINING PADA JUMLAH PENDUDUK. 1(3), 199–207.
Talino, S. P. (2020). PENERAPAN DATA MINING PADA JUMLAH PENDUDUK MISKIN DI. March 2021. https://doi.org/10.46306/lb.v1i3.42
Utara, S. (2019). Metode K-Means Untuk Pengelompokan Masyarakat Miskin Dengan Menggunakan Jarak Kedekatan Manhattan City Dan Euclidean ( Studi Kasus Kota Binjai ).
Wibowo, A. E., & Habanabakize, T. (2022). K-MEANS CLUSTERING UNTUK KLASIFIKASI STANDAR KUALIFIKASI EDUCATION DAN PENGALAMAN KERJA GURU. 7, 152–163.
N. M. Br Tarigan, B. Sinaga, E. Panggabean and J. R. Sagala, "Development Of Scholarship Sustainability Analysis Application Every Semester On STMIK Pelita Nusantara Students," 2022 IEEE International Conference of Computer Science and Information Technology (ICOSNIKOM), Laguboti, North Sumatra, Indonesia, 2022, pp. 1-8, doi: 10.1109/ICOSNIKOM56551.2022.10034918.
Downloads
ARTICLE Published HISTORY
How to Cite
Issue
Section
License
Copyright (c) 2023 Nera Mayana Br. Tarigan, Santa Elisa Br. Tarigan, Alfrida P. Simatupang
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.