<![CDATA[Ensuring a sufficient supply of blood is a crucial aspect of providing health services. However, the large demand for blood is sometimes difficult to fulfill for one of the work units in the Indonesian Red Cross (PMI), namely the Blood Transfusion Unit. Therefore, blood demand prediction is needed to assist the blod transfuse unit in preparing sufficient blood stock. This study uses the ARIMA-Kalman Filter model to anticipate the quantity of blood demand for Blood Transfusion Unit PMI. The observations modeled in this study are daily observations of the amount of blood demand with the period January 1 to December 26, 2023 as an in-sample of 360 observations and blood demand for the period 27 to 31 December 2023 which amounted to 5 observations as an out-sample used to evaluate the model. The analysis’s findings indicate that the model obtained for predicting the amount of blood demand is the ARIMA (0,0,2) model, then the model parameters are estimated using Kalman Filter. The model used fulfills the diagnostic test and obtained a MAPE value of 15.021% in predicting out-sample data. Thus it can be concluded that the model used is in the very good category and is suitable for prediction. Furthermore, predictions are made for the next three days on the number of blood requests at Blood Transfusion Unit PMI Pontianak City to help health services prepare blood stocks for patients in need.]]>
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