Penerapan Metode K-Means Clustering Untuk Mengelompokkan Data Kelayakan Penerima Bantuan Renovasi Rumah

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

Implementasi Algoritma K-Means Clustering Dalam Pengelompokan Data Kerusakan Rumah Akibat Bencana Alam Di Kabupaten Cirebon

“…Dalam penelitian yang dilakukan oleh [3] Dalam riset yang dilakukan oleh [4] di tahun 2023 dalam jurnal " Penggunaan Metode K-Means Clustering dalam Pengelompokkan Data Kelayakan Penerima Bantuan Renovasi Rumah". Melalui pemodelan dan pengujian yang telah dilakukan, hasilnya menunjukkan bahwa dari total data 170 data yang digunakan, terdapat dua klaster yang dihasilkan.…”