Comparison SAW and MOORA Methods with Attribute Weighting Using Rank Order Centroid in Decision Making

Abstract

This study comparing the performance of SAW and MOORA methods are in the decision-making process against the evaluation of teacher assistant performance. Then, applying Rank Order Centroid (ROC) is to overcome the process of weighting attributes in decision-making. Subsequently, the data has used by Teaching Assistant Evaluation obtained from UCI Machine Learning Repository, which has 151 instances, five attributes, and 1 class label with multivariate type dataset. The results of testing the calculation of SAW and MOORA methods, obtain the different results where A134 is the best alternative in the calculation of SAW and A132 is the best alternative in the calculation of MOORA. Afterward, if viewing based on running time, the execution process of the SAW method is 0.06 seconds,while the execution process of the MOORA method is 0.02 seconds. In this research, both methods get the same results in ranking, but base on running time, the MOORA method is faster than the SAW method.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 51 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.