Implementasi Algoritma K-Means Menggunakan RapidMiner untuk Klasterisasi Data Obat Pada Rumah Sakit Royal Prima

Abstract

Efficient management of drug data is a crucial element in hospital operations to ensure the availability and proper use of medications. This research aims to implement the K-Means clustering algorithm using RapidMiner software to cluster drug data at RS Royal Prima. The dataset includes information such as drug type, category, price, and intake frequency. The clustering process begins with data preprocessing stages, such as cleaning and normalization. The optimal number of clusters is determined using the elbow method and silhouette analysis. The clustering results show that drug data can be grouped into several large clusters based on specific characteristics. This analysis helps identify patterns of drug use that can support clinical decision-making and improve inventory management. This implementation demonstrates that using RapidMiner to cluster pharmaceutical data is effective and provides valuable insights to enhance hospital operations.