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All Journal Jurnal Informatika Ekonomi Bisnis Jurnal Informatika Ekonomi Bisnis
Abdul Azis Said
Universitas Putra Indonesia YPTK Padang
Economics, Econometrics & Finance

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Klasterisasi Dana Bantuan Pada Program Keluarga Harapan (PKH) Menggunakan Metode K-Means Abdul Azis Said; Sarjon Defit; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.893 KB) | DOI: 10.37034/infeb.v3i2.66

Abstract

The Family of Hope Program (PKH) is a program that aims to reduce poverty and improve the quality of human resources. Optimizing the provision of assistance in accordance with the expectations of those in need. Data on the poor or integrated social welfare data is needed as a reference for grouping. This study aims to make it easier for the selection team to provide assistance in accordance with the predetermined criteria whether or not they deserve to receive the assistance. The data used in the study is data from 2019. The data processing in this study uses the K-Means Clustering method with 3 clusters, namely Cluster 1 (C1) Nearly Poor Households (RTHM), Cluster 2 (C2) Poor Households (RTM), Cluster 3 (C3) Very Poor Households (RTSM). The results of the clustering process with 2 iterations state that for Cluster 1 the amount of data is, for Cluster 2 the amount of data, and for Cluster 3 the amount of data. So this research is very helpful in relocating targeted assistance according to the family hope cluster.
Klasterisasi Dana Bantuan Pada Program Keluarga Harapan (PKH) Menggunakan Metode K-Means Abdul Azis Said; Sarjon Defit; Yuhandri Yunus
Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (2021)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.893 KB) | DOI: 10.37034/infeb.v3i2.66

Abstract

The Family of Hope Program (PKH) is a program that aims to reduce poverty and improve the quality of human resources. Optimizing the provision of assistance in accordance with the expectations of those in need. Data on the poor or integrated social welfare data is needed as a reference for grouping. This study aims to make it easier for the selection team to provide assistance in accordance with the predetermined criteria whether or not they deserve to receive the assistance. The data used in the study is data from 2019. The data processing in this study uses the K-Means Clustering method with 3 clusters, namely Cluster 1 (C1) Nearly Poor Households (RTHM), Cluster 2 (C2) Poor Households (RTM), Cluster 3 (C3) Very Poor Households (RTSM). The results of the clustering process with 2 iterations state that for Cluster 1 the amount of data is, for Cluster 2 the amount of data, and for Cluster 3 the amount of data. So this research is very helpful in relocating targeted assistance according to the family hope cluster.
Co-Authors Sarjon Defit Yuhandri Yuhandri