Modification of Grey Relational Analysis (GRA) Method for Improved Decision Making

The main purpose of this study is to modify the Grey Relational Analysis (GRA) method by using symmetry points to improve its accuracy in decision-making. This modification aims to enhance the sensitivity of GRA in measuring the proximity between alternatives and the ideal solution by considering symmetry in the data. By applying symmetry points, this research improves the way GRA handles imbalanced data variations, resulting in more accurate and objective analysis. The novelty of this approach lies in the integration of the concept of symmetry points into the calculation of relational coefficients, which has not been previously applied in the context of GRA, thus enabling a more adaptive mapping of the data distribution characteristics. The ranking results from the selection of the best employees show that A4 employees are in first place with a score of 0.1254. The results of the comparison of Spearman's correlation values for five different methods. The highest result was achieved by the GRA-SP method with a correlation value of 1, followed by GRA-Entropy which was close to the maximum value of 0.9667. The GRA-LOPCOW method is in third place with a correlation value of 0.8, while GRA-RS has a correlation of 0.75. The lowest correlation value was found in the GRA-ROC method with 0.575. This shows that the GRA-SP method has the strongest correlation, while the GRA-ROC shows the weakest relationship among the methods compared.