Implementasi Metode K-Modes Dalam Pengelompokan Penerima Bantuan Langsung Tunai

 (*)Ika Nurul Hidayah Mail (Universitas Tanjungpura, Pontianak, Indonesia)
 Cucu Suhery (Universitas Tanjungpura, Pontianak, Indonesia)
 Rahmi Hidayati (Universitas Tanjungpura, Pontianak, Indonesia)

(*) Corresponding Author

Abstract

Direct Cash Assistance is a government assistance program that is given to underprivileged people. Assistance is distributed in the form of cash assistance sourced from village funds. In the process of distribution BLT funds, there were obstacles faced by the village, namely incomplete data on BLT recipients. Based on these constraints, a data survey of BLT recipients was carried out using predetermined variables. There are 20 variables used for BLT recipients. Based on the survey results, there was a lot of data that had something in common, making it difficult for the Sungai Dungun village to group BLT recipients. Therefore we need a system that can grouping BLT recipient data. The method used for grouping data on this system is the K-Modes method. The test uses the Davies Bouldin Index (DBI) to know out whether the cluster results are good or not. Based on the results of the DBI test, there is a minimum value generated in grouping using 4 groups with a value of 1.25858. Grouping with 4 groups resulted in a very worth it group of 101 heads of households, a feasible group totaling 40 heads of households, a moderately feasible group totaling 44 heads of households, and an unfeasible group totaling 15 heads of households.

Keywords


BLT; DBI; Village; K-Modes; Clustering.

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