A Framework of Subjective Performance Evaluation Using Fuzzy Technique

This research proposes the framework of subjective performance evaluation using fuzzy technique for ranking the attributes of different types of datasets under a
multi-criteria environment. Some previous studies on fuzzy techniques have been attempted in assessment and evaluation methods. The techniques such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted in these fuzzy evaluation methods. However, research that discover a
scaling measurement which can express the subjectivity element and integrate the organisation‘s objectives and goals into the evaluation processes by utilising the
fuzzy rule in the subjective evaluation method seem limited. Hence, this framework uses the application of fuzzy sets, and approximate reasoning to determine the
performance evaluation of various characteristics in decision-making. The framework based upon fuzzy sets has initiated the idea of membership set score valued
evaluation of each criterion alternative enables to include requirements which are incomplete and imprecise. The approximate reasoning of the method allows decision maker to make the best choice in accordance of human thinking and reasoning processes. The method introduces an approach of normalising data using
similarity function which dampens the extreme value that exists in the data. The framework is suitable for dealing with evaluations in situations that involve subjectivity, vagueness and imprecise information, such as the grading system of evaluation which involves subjectivity, vagueness and imprecise information, such as the grading system evaluation which involves many hedges like "good", "bad" and "satisfactory".