Modified LFPP to improve the accuracy of matrix pairwise comparison consistency index in the usability evaluation

Usability evaluation focuses on how well users can learn and use products to achieve their goals. Evaluation of e-commerce website usability can be done using the Fuzzy Analytical Hierarchy Process (FAHP) method. Usability is considered a multi-criteria problem due to its complex structure. Logarithmic Fuzzy Preference Programming (LFPP), a non-linear programming approach, is one of the FAHP methods for weighting criteria. However, deficiencies in the LFPP method, in some cases, result in a consistency value of 0 from a consistent fuzzy comparison matrix, which should be greater than 0. This study modifies the LFPP method with the Modified LFPP (MLFPP) models. Modifications were made as a development of the LFPP method in improving the accuracy of the consistency index (*) before weighting criteria. The MLFPP makes improvements to the functional constraints, while at the same time improving the determination of criteria weights. The MLFPP model uses arctan to limit functions to improve consistency index. The test results show that the MLFPP can improve the accuracy of the consistency index values in the pairwise comparison matrix given by experts to be more than 0, with an average increase of 14.9. The amount of consistency index (*) changes has improved the usability score by 6.59. © 2020, Intelligent Network and Systems Society.