Measuring Students' Perception on Mathematics Learning Using Fuzzy Conjoint Analysis

Measuring Students' Perception on Mathematics Learning Using Fuzzy Conjoint Analysis


  • Zurina Kasim Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Nur Liyana Muhamad Sukri Universiti Teknologi MARA, Perlis Branch, Arau Campus



fuzzy conjoint analysis, perception, perception measurement


Mathematics courses are widely applied in the overall sector because mathematics is not only about the calculation or formulation, but also helps in solving problems using mathematical modelling. Students need to have a good understanding of the theory of mathematics in order to produce the best results. In the world of digitization, subjects in science, technology, engineering and mathematics have become Malaysia’s agenda in the preparation to compete globally. Empowering in these subjects enables the creation of innovators of the future, hence creating job opportunities in the digitization world. However, the academic institutions have been facing a critical problem in potential growth of achieving the mission and vision in enhancing the students’ performance when it is related to the students’ interest. This study focuses on students’ perception toward mathematics learning among 60 undergraduate management mathematics major’s students at UiTM Perlis using fuzzy set conjoint analysis. The attribute in each dimension is ranked according to the highest similarities values. The finding showed that students were rated neutral toward the preparation before class (student’s attitude); strongly agree that the lecturers are knowledgeable and well prepared before class (lecturer’s role); and rated neutral on female students are more qualified mathematician and their passion toward mathematics but strongly agreed that mathematics is difficult to understand in short period of time (student’s perspective).


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How to Cite

Kasim, Z., & Muhamad Sukri, N. L. (2022). Measuring Students’ Perception on Mathematics Learning Using Fuzzy Conjoint Analysis. Journal of Computing Research and Innovation, 7(1), 82–92.



General Computing