Mamdani Fuzzy Analysis and Application for Assessing Student Intelligence Levels

Abstract

Determining the intelligence level of students is one of the important steps in supporting the evaluation process of learning in a more objective and systematic manner. However, intelligence assessment is often still conducted conventionally and tends to be subjective because it is influenced by many criteria that cannot always be precisely evaluated. This research aims to analyse and implement the Fuzzy Mamdani method in determining the intelligence level of students based on several assessment indicators. The Fuzzy Mamdani method was chosen because it can process data that is vague and uncertain into more logical and structured decisions. The research stages include data collection, determination of input and output variables, formation of fuzzy sets, formulation of fuzzy rules, inference process, and defuzzification to produce the final value of student intelligence levels. The variables used in this study include academic scores, activity, discipline, and comprehension ability as inputs, while the output is the category of student intelligence levels. The research results show that the Fuzzy Mamdani method can be applied to assist in the decision-making process in determining students' intelligence levels more flexibly, objectively, and efficiently. The system built is capable of providing intelligence level recommendations based on the combination of scores from each predetermined criterion. Thus, the implementation of the Fuzzy Mamdani method is expected to become a decision-support solution for the school in conducting student assessments more accurately.