Algoritma K-Means Clustering dalam Memprediksi Penerima Bantuan Langsung Tunai (BLT) Dana Desa
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Keywords:
Clustering, K-Means, Prediction, Direct Village Fund, Cash Assistance
AbstractTaluk Village, Lintau Buo Subdistrict, Tanah Datar Regency is one of the villages that carries out the distribution of the Village Fund Direct Cash Assistance (BLT-DD) program. This direct cash assistance is one of the government programs whose funds are sourced from village funds whose distribution is to the underprivileged or poor in order to overcome economic recovery for people affected by the pandemic. However, in the evaluation of its implementation in 2021 and 2022, many problems were found in its distribution, especially in determining this assistance to the recipient community. The problems that arise are caused by the occurrence in data processing that uses a direct determination system or mechanism in deliberation by the village government to determine the priority community as recipients of the many who propose as applicants to the nagari government to get this assistance. Besides that, there are also problems such as errors in recipient criteria and often this program is not targeted at the recipients. The K-Means Clustering method is very precise in implementing this BLT-DD beneficiary predictor, because this method is one of the methods used in data grouping as a reference in decision makers for clustering large amounts of data, and in the end it will cluster recipients based on 3 clusters, namely worthy, considered and unworthy. The purpose of this study was to predict the right target recipients of BLT-DD. The data processed is the data proposed by the recipients of the BLT-DD Taluk Village in 2022. Based on the results of data processing using PHP MYSQL Software, from a sample of 25 data, 11 data are produced which are included in cluster 1 with the status of the beneficiary being said to be feasible, 5 data that are classified as eligible. including cluster 2 with considered recipient status and as many as 9 data belonging to cluster 3 with unfit status. From the test results obtained an accuracy rate of 83.33 % so that it can be recommended to assist the government of the village guardian in making policies. Downloads
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Published
2022-12-31
Section
Articles
How to Cite
Filki, Y. (2022). Algoritma K-Means Clustering dalam Memprediksi Penerima Bantuan Langsung Tunai (BLT) Dana Desa. Jurnal Informatika Ekonomi Bisnis, 4(4), 166-171. https://doi.org/10.37034/infeb.v4i4.166
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