Comparison between Multiple Attribute Decision Making Methods through Objective Weighting Method in Determining Best Employee (International Journal of Innovative Research in Computer Science & Technology, 2023)
Multiple Attribute Decision Making  (MADM) is a popular method to be selected in numerous  studies in solving decision-making cases. Methods like  SAW, WASPAS, SMART, and WP are preferred among  researchers to be used for many purposes. However, the best  method still not compared in determining best employee.  Hence, the study conducted the comparison between the  methods by using the Rank Similarity Index (RSI). The index  is used to express the most appropriate method. In terms of  weighting, we propose the D-CRITIC method as the tool to  support the comparison procedure. Moreover, we select the  bus driver as the sample case of the study with total of 10  candidates are nominated to be chosen as the best. The  company has given the rank list before, so we just compare  the actual rank with the result of MADM methods  calculations. The result shows that SAW and WASPAS are  the methods with the highest similarity towards the rank.  Furthermore, these methods also reach the great score of the  RSI between the others.
Keywords: MADM; Comparison; Best Employee; Objective Weighting; RSI