Klasterisasi Data Obat dengan Algoritma K-Means (Kasus pada UPTD Puskesmas Curug) - kastiawan, Nurhayadi; Huda, Baenil; Novalia, Elfina; Nurapriani, Fitria (J-SAKTI (Jurnal Sains Komputer dan Informatika), 2024)
Managing drug supplies is very important because it minimizes drug losses in institutions such as health centers, pharmacies and hospitals, so that drugs of any type are in accordance with the quantity needed. The research aims at grouped drug data, where this case study was carried out at the Curug Health Center UPTD which will be used as a guide in submitting a drug import plan at this health center. The data processed in this research is the 2022 annual report, drug needs plan and proposed drug needs (RKO 2023) at the Curug Health Center UPTD. The data in this research was processed by the K-Means algorithm with the rapidminer tool, where this technique data is grouped by collecting data into clusters. The results obtained were that Cluster 0 was a very low cluster which contained 14 drug items, then Cluster 1 with 12 drug items was a low cluster, Cluster 3 with 2 drug items was a high cluster and Cluster 2 was the highest cluster with 2 items drug.