Klasterisasi Obat Berdasarkan Tipe dan Komposisi Sejenis pada Bagian Farmasi Rumah Sakit Queen Latifa

Nurul Imam Prayogo, Puji Winar Cahyo, Landung Sudarmana, Nurul Fatimah
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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.
拉提法王后医院药剂部按类型和成分对药物进行分组
保持和提高医疗服务质量的一个重要因素是提供充足的药物。药品是提供医疗保健服务的重要组成部分,与药品相关的费用在总体医疗保健成本中占很大比重。实施数据挖掘可以帮助分析药品使用情况,从而获得可用于规划和控制药品库存的信息,其中一种方法就是使用 K-Means 算法。K-Means 算法是数据挖掘中最流行、应用最广泛的聚类方法。这项研究旨在帮助药剂师识别具有相似特征和组成的药品类型组。因此,可以更有效、更准确地对大量药物进行分类。此外,根据相似特征和成分对药物进行分组后,药房人员可以轻松监控特定药物的供应情况,并采取适当措施管理医院的药物供应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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