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All Journal Teknomatika: Jurnal Informatika dan Komputer
Imam Prayogo, Nurul
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Computer Science & IT

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Klasterisasi Obat Berdasarkan Tipe dan Komposisi Sejenis pada Bagian Farmasi Rumah Sakit Queen Latifa Imam Prayogo, Nurul; Winar Cahyo, Puji; Sudarmana, Landung; Fatimah, Nurul
Jurnal Teknomatika Vol 13 No 2 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i2.1120

Abstract

One important element in maintaining and improving the quality of healthcare services is the availability of adequate medication. Drugs are a crucial component used in the provision of healthcare services, and the expenses associated with them constitute a significant portion of overall healthcare costs. The implementation of data mining can aid in analyzing drug usage to obtain information that can be utilized for planning and controlling drug inventory, with one of the methods being the utilization of the K-Means algorithm. The K-Means algorithm is the most popular and widely used clustering method in data mining. This research aims to facilitate pharmacy personnel in identifying groups of drug types with similar characteristics and compositions. As a result, the categorization of a large number of drugs can be performed more efficiently and accurately. Moreover, with the grouping of drugs based on similar characteristics and compositions, pharmacy personnel can easily monitor the availability of specific medications and take appropriate actions in managing drug supplies at the hospital.
Co-Authors Landung Sudarmana, Landung Nurul Fatimah Winar Cahyo, Puji