Evaluating student's academic achievement by a non-additive aggregation operator

Abstract

Abstract. In the context of multi-criteria decision making (MCDM), the average method used in Integrated Students Information System (ISIS) can be classified as an additive measure where the students' academic achievement are aggregated based on the assumption that there is no interaction among the evaluation criteria or the criteria are independent. This method is not suitable to be used if the schools look for equilibrium in their students' achievement. Thus, the non-additive aggregation operator is chosen to analyze students' academic achievements by further taking into accounts the interactions between the subjects. The measures of interaction were represented as λ-fuzzy measures. The effectiveness and success of this non-additive measures can be recognized by comparing the results of the new ranking which was obtained by nonadditive aggregation operator with the current approach of ranking that were based on the global scores using average score method. Throughout this study, it could be postulated that employing the non-additive aggregation operators to obtain an overall evaluation is more suitable because this method able to deal with interactions among subjects whereas the average method only assumes that there is no interaction between subjects or the subjects must be independent.

A Review on Picture Fuzzy Aggregation Operators

“…All the PFAOs mentioned above use additive AOs such as Weighted Average (WA) operator [75], Weighted Geometric (WG) operator [76], as well as Ordered Weighted Average (OWA) operator [77] that linear in nature and relying on the assumption that decision-makers' preferences are defined by an independence axiom [78,79]. The authors Abdullah et al, [80] stated one of the major…”