<![CDATA[Hospitals today have widely adopted inventory systems for managing drug supplies, which involve the process of big data analysis to identify relevant patterns, relationships, and trends in the drug inventory data. The goal is to optimize stock management, reduce waste, and ensure the availability of the right medications at the right time. Effective and efficient drug inventory management is a crucial aspect of hospital operations, ensuring timely availability of medications and minimizing the risks of shortages or overstocking. In this study, the Naïve Bayes method was chosen for its ability to handle large and complex datasets and produce accurate predictions. The research process involved several stages: problem identification, problem formulation, data collection, model classification creation, application development, model implementation, research testing, and report preparation. The findings of this study demonstrate the significant potential of data mining in inventory management within the healthcare sector.]]>
Copyrights © 2024
