Determining Lecturers’ Research Linearity Using Simple Additive Weighting and Technique for Order Preference by Similarity to Ideal Solution - Narulita, Siska; Nugroho, Ahmad; Abdillah, M. Zakki (Scientific Journal of Informatics, 2024)
Purpose: This study aims to conduct a comparative analysis of the decision-making methods of Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and build a decision support system that can be used to determine the linearity of lecturers’ research in their scientific fields. The analysis aims to assist relevant institutions in determining research linearity and guiding lecturers in their research policies and directions. Methods: This study compares the performance of the SAW and TOPSIS methods, against the alternative ranking of lecturers’ research linearity. The performance of both methods was measured using accuracy and MSE, where a high accuracy value indicates that the method performs better and the value of MSE is small or close to zero indicating a better relevance. Result: The results showed that the SAW method has a better accuracy value of 100% and an average MSE value of 0.13. At the same time, the TOPSIS method has an accuracy value of 33% and an average MSE value of 0.58. Novelty: This study provides knowledge about the effectiveness and efficiency of decision-making methods to determine the lecturers’ research linearity, as a guideline for related institutions regarding research policy making. In addition, the results of this study also provide a framework for evaluating the recent decision-supporting method and improving the understanding of the implementation and performance of the methods.