Classification and Regression Trees (CART) Method in the Classification Process of Blood Control Candidates

The classification of blood donor candidates is a crucial process that requires thorough health checks and assessments. Implementing a reliable and efficient classification system for blood donor candidates is essential to ensure the safety and well-being of both the donor and the recipient. This study focuses on implementing the Classification and Regression Trees (CART) method in the classification process of blood control candidates. Given the complex series of health checks involved in the process, which includes age, weight, blood pressure, pulse rate, and blood tests (hemoglobin, blood type, and rhesus), a reliable and efficient classification system is necessary. This research demonstrates the successful implementation of the CART method in developing an expert classification system for blood donor candidates. The system achieved an accuracy value of 98.03%, making it a highly effective and reliable tool for improving blood control candidate classification accuracy and efficiency. This research has significant implications for enhancing the safety and success of blood transfusions.