Abstract
 The hospital is a health service institution for the community with its own characteristics that require a variety of resources in carrying out its activities. One of the most important is health equipment. Medical devices are supporting aspects that support the implementation of health services. PALI Regional General Hospital is a Type D hospital, which needs to manage its medical devices. Kepmenkes Regulation No. 004 / MENKES / SK / 1/2003 concerning health policy and strategy on decentralization in the health sector states that one of the strategic objectives is the effort to organize health management in the decentralization era is to develop sub-systems of maintenance and optimization of utilization of health facilities and equipment. The amount of medical device data can only be estimated from the many or at least the available medical devices (stock), because the needs of each year are different. This results in not all the needs of medical devices being met and often additional stocks occur while the amount of APBD has been divided for each institution. So to anticipate this it is necessary to predict the need for medical devices in PALI District Hospital. If the status of medical device needs can be predicted early, the hospital can minimize data redundancy (repetition of data) and information can be up to date (update). In this study, the authors will predict medical devices in Pali District Hospital using the classification method in data mining based on the Algortima Linear Regression model to get the most accurate test results.Keywords : Prediction, Medical Devences, Linear Regression Algorithm, Naive Bayes
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.