The Application of Prediction Data Miningbed Occupancy Rate of Covid-19 Patients in West Java - Amelia Hani; Ayi Ratna K; Cristina Juliane (Budapest International Research and Critics Institute-Journal (BIRCI-Journal), 2022)
The Covid-19 pandemic in 2020 is a complex health problem and requires fast handling. Covid-19 patients who receive treatment in hospitals have different conditions and severity. This affects the handling actions that will be carried out by medical officers. The large number of patients and the lack of medical personnel and the availability of beds have resulted in the need for technological support to help predict the status of patient bed availability based on their condition so that treatment is concentrated on patients who are very critical and require rapid treatment. This research applies prediction techniques from data mining disciplines to predict a spike or decrease in BOR (Bed Occupancy Rate). Prediction using the C4 algorithm. 5 was applied to build a model based on the Covid-19 bed availability dataset. The Covid-19 BOR (Bed Occupancy Rate) dataset in West Java was obtained from Opendata.jabarprov.go.id and applied using Rapid Miner. The model built can predict the status of bed availability based on the occupancy of the patient's hospitalization. The results of this study indicate that predictions using the C4.5 Algorithm method have a high level of accuracy of %.