PIEDADE, Griselda Anastasia Da (2023) Model Regresi Untuk Memprediksi Persediaan Darah Di UTD PMI Provinsi Nusa Tenggara Timur. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.
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Abstract
The role of UTD PMI East Nusa Tenggara Province as a provider of blood services requires that this health unit be able to meet the needs of blood because it is closely related to the health and safety of a person's life. One of the important problems faced by UTD PMI NTT Province is the uncertainty of demand for blood, so a way is needed to guarantee its availability. This is due to the nature of blood which is perishable and cannot be reproduced, and its availability is highly dependent on donors. This study produced 36 linear regression models, based on the MAPE value of each prediction result. Recommendations The regression model used to predict blood supply for 4 blood groups, namely blood A, B, AB and O. The first regression model Y = 811.174+14.4261X Predicts blood group A supply, with training data for the last 2 years. The MAPE value is 21.8% where the criteria indicate a reasonable prediction. secondly, Y=1296.55+19.6469X Predicting blood group B stock, with training data for the last 1 year. The MAPE value is 13.4% where the criteria show a good prediction. Third Y = 235.91 + 1.98687X Predict the supply of blood type AB, with training data for the last 3 years. the MAPE value is 20.6% where the criteria indicate a reasonable prediction. And finally Y = 1567.36 + 19.2013X Predicting blood type O stock, with training data for the last 2 years. and the MAPE value is 17.0% where the criteria indicate a reasonable prediction.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Prediction, Regression Model, Blood, Simple Linear Regression,MAPE. |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Fakultas Teknik > Program Studi Ilmu Komputer |
Depositing User: | S.Kom Griselda Anastasia Da Piedade |
Date Deposited: | 29 Aug 2023 00:19 |
Last Modified: | 29 Aug 2023 00:19 |
URI: | http://repository.unwira.ac.id/id/eprint/13318 |
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