Stock Prediction Of Single-Use Medicine Using Autoregressive Integrated Moving Average

Stock Prediction of Single-Use Medicine Using Autoregressive Integrated Moving Average the(3, 1, 3) model, derived from the (p,q,d) model where p is the AR level, d is the process level that makes the data stationary, and q is the MA level. The (3, 1, 3) model used provides quite good results the ARIMA (3, 1, 3) model can be a good tool to predict the need for consumable drug stocks show that the ARIMA (3, 1, 3) model gives good results,log likelihood values and information criteria indicating that the model is reliable. Predictions for the demand for consumable drugs in 2025 show a downward trend, Requires further attention to understand the causes. health centres can plan drug procurement more precisely and efficiently meet patient needs without experiencing overstocks or shortages.