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Gina Sonia
Universitas Islam Negeri Sumatera Utara, Medan
Computer Science & IT

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Penerapan Metode K-Means Clustering Untuk Mengelompokkan Data Kelayakan Penerima Bantuan Renovasi Rumah Gina Sonia; Raissa Amanda Putri
Building of Informatics, Technology and Science (BITS) Vol 5 No 2 (2023): September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i2.4298

Abstract

The government provided one form of assistance, namely the renovation of houses in the Kuala Bangka Village area in Kualuh Hilir District, North Labuhan Batu Regency from 2015 until now. However, with this assistance, Kuala Bangka Village sometimes has problems in determining the feasibility of receiving assistance from the government, therefore the author will conduct research by categorizing the eligibility of recipients of house renovation assistance by applying the K-Means algorithm. The K-Means Clustering algorithm is an algorithm that can classify data accurately according to the previous problem. The grouping aims to determine cluster 0 and cluster 1 as recipients of house renovation assistance, cluster 0 is feasible and cluster 1 is not feasible. The attributes used in this research are number of family members, employment, housing conditions, and income. The results obtained from 170 data were cluster 0 with 91 data and cluster 1 with 79 data. From these results, 91 people were eligible to receive home renovation assistance and 79 were not eligible to receive home renovation assistance
Co-Authors Raissa Amanda Putri