Artificial Neural Network Based Prediction Model Back Propagation on Blood Demand and Blood Supply

Artificial Neural Network Based Prediction Model Back Propagation on Blood Demand and Blood Supply

neural network; backpropagation; blood demand; blood supply

The balance between blood demand and supply at the Indonesian Red Cross Blood Transfusion Unit (UTD-PMI) is crucial.
This condition needs to be maintained to reduce unused or expired blood supplies. Despite the situation at UTD-PMI, where
the blood supply exceeds the demand, there is still a shortage of blood when needed by patients. This research aims to model
the prediction of blood demand and supply for each blood type using the Back Propagation artificial neural network approach.
Data from the last 3 years, from 2020 to 2022, were utilized in this research process. There are three stages in this research
process. The first stage involves the training process, using data from January 2020 to December 2021. The testing process
utilizes data from January 2021 to December 2022. The prediction process involves displaying forecasted data for the next 12
months from January to December 2023. The accuracy of the calculations is assessed using the Mean Square Error (MSE).
Ultimately, the research results present the prediction model for the four blood types regarding blood demand and supply.
These findings can serve as a reference for regulating future blood donation activities carried out by the UTD-PMI.

Frengky Tedy, Patrisius Batarius, Ign. Pricher A. N. Samane, Alfry Aristo Jansen Sinlae

http://jurnal.iaii.or.id

Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association

December 2023

Sri Wahyuni

ISSN Media Electronic: 2580-0760

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