Peramalan Jumlah Kebutuhan Persediaan Kantong Daerah (Blood Bag) di Palang Merah Indonesia Kota Yogyakarta
Keywords:
Forecasting, Exponential Smoothing, Moving Average, Linear RegressionAbstract
Blood is an important part of the human body, where if problems occur due to disease, accidents, injuries during natural disasters that cause bleeding, blood transfusions will be required. To encourage blood transfusion activities to remain smooth, it is necessary to carry out good management in controlling the number of blood bag supplies. To overcome this, this research conducted a forecast of the need for blood bags in the Indonesian Red Cross (PMI) Yogyakarta City. The forecasting methods applied in this research are exponential smoothing, moving average and linear regression. Based on the data processing carried out, the results showed that the linear regression method was the best method for predicting the need for the number of blood bags in the Indonesian Red Cross (PMI) Yogyakarta City compared to the exponential smoothing and moving average methods. This is because the error level obtained from the calculation shows that the Mean Absolute Deviation (MAD), Mean Squarred Error (MSE) and Mean Absolute Percentage Error (MAPE) values of the linear regression method are the lowest compared to other methods. The results obtained from forecasting the need for blood bags are that 110 units of blood bags are needed to facilitate blood donations in the next period, namely in the 14th week.
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References
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