Implementasi Algoritma K-Means Untuk Klasterisasi Data Obat Puskesmas Kotabaru

Muhamad Dicky Kurniawan(1*), Bayu Priyatna(2), Fitria Nurapriani(3),

(1) Universitas Buana Perjuangan Karawang, Indonesia
(2) Universitas Buana Perjuangan Karawang, Indonesia
(3) Universitas Buana Perjuangan Karawang, Indonesia
(*) Corresponding Author

Abstract


Drug management is one of the things needed to manage drug supplies. Proper planning of drug needs makes drug procurement efficient and effective so that drugs are available in sufficient types and quantities as needed and easily obtained when needed. The purpose of this study was to classify drug data at the Kotabaru Health Center which can be used as a reference in making decisions in planning and controlling drug needs at the Health Center. The data used in this study are the Kotabaru Health Center annual report data from 2019 to 2021. Data processing in this study uses the K-means clustering method with rapidminer tools which is a data grouping technique by dividing the existing data into one or two forms. more clusters. The results of this study divide the drug data into 4 clusters, namely the first cluster (C0) with very low usage consisting of 27 drugs, the second cluster (C2) with low usage consisting of 6 drugs, the third cluster (C3) with high usage consisting of 1 drug, and the fourth (C2) with the highest usage consisting of 1 drug.

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DOI: http://dx.doi.org/10.30645/j-sakti.v7i2.693

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