Performance of Moving Average and Exponential Smoothing Methods in Forecasting Demand for Blood Components
Author: I Gede Totok Suryawan*, Ni Luh Shintadewi Pratiwi, I Gede Iwan Sudipa, Ida Bagus Gede Anandita
Prodi Informatika, Fakultas Teknologi dan Informatika, Institut Bisnis dan Teknologi Indonesia, Denpasar, Bali, Indonesia.
Published Date: 2024-11-30
Keywords: Forecasting, Blood components, Mean Absolute Percentage Error (MAPE). Exponential Smoothing, Moving Average.
Abstract:
The development of population growth in Indonesia affects the need for blood which must be stored as a supply. Blood supply management in Indonesia is managed by PMI (Indonesian Red Cross). PMI is a national association in Indonesia that operates in the fields of social humanity. The Importance of blood needs makes PMI maintain blood supplies. UTD PMI Denpasar City experienced an excess of blood supplies so blood that had passed its expiration date was destroyed. Therefore, this research can provide information and recommendations to UTD PMI Denpasar City in controlling the supply of blood components. The methods used in this forecasting are the Moving Average and Exponential Smoothing methods with the data studied being the number of requests for blood components from January 2021 to April 2023. In the analysis to get the right forecasting method, the smallest MAPE value was obtained for the respective forecast demand. each. each blood component is Exponential Smoothing with an alpha of 0.9, including Packed Red Cell getting a MAPE value of 1.34%, Fresh Frozen Plasma getting a MAPE value of 6.70%, and Trombocyte Concentrat obtained a MAPE value of 7.28%.
