An Extended Consistent Fuzzy Preference Relation to Evaluating Website Usability

Wahyuningrum, Tenia and Azhari, Azhari and Suprapto, Suprapto (2019) An Extended Consistent Fuzzy Preference Relation to Evaluating Website Usability. (IJACSA) International Journal of Advanced Computer Science and Applications, 10 (9). pp. 109-116. ISSN 2156-5570

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Abstract—In the current era, website developers recognize usability evaluation as a significant factor in the quality and success of e-commerce websites. Fuzzy Analytical Hierarchy Process (FAHP) is one method to measure the usability of the website. Several researchers have applied Logarithmic Fuzzy Preference Programming (LFPP) approach to deriving crisp weight from fuzzy pairwise comparison matrix of FAHP approach. However, there is a lack of LFPP method in determining the consistency index of the decision-maker judgment. In some cases, LFPP method will produce a consistency value of 0 from consistent fuzzy comparison matrices. This value indicates there is a contradiction with what the previous researchers have said, that a constant matrix value should be more than 0. This research proposes the extended Consistent Fuzzy Preference Relation (ECFPR) to assist the regular judgment for specifying the weights in measuring ecommerce website usability. The CFPR method used to form a new pairwise comparison matrix. ECFPR was calculating the lower and upper values at the fuzzy triangular number from the only n-1 comparison, where n is the number of criteria. The numerical experiment showed that the consistency index obtained by extended CFPR method was more significantly better than LFPP method. It was revealed that the optimal value always more than 0. The consistency index of ECFPR method has a higher mean value than LFPP, so that the use of the ECFPR method can improve the amount of consistency comparison matrices. The ECFPR method was also successfully implemented with the experimental case on evaluating ecommerce website usability. Keywords—Usability; e-commerce; website quality; logarithmic fuzzy preference programming; consistent fuzzy preference relations

Item Type: Article
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Informatics
Depositing User: Tenia Wahyuningrum
Date Deposited: 24 Aug 2022 08:45
Last Modified: 24 Aug 2022 08:45

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