The Weights Detection of Multi-criteria by using Solver - Fachrurrazi Fachrurrazi; Yuwaldi Away; Saiful Husin (Institute of Advanced Engineering and Science, 2017)
Multi criteria, which are generally used for decision analysis, have certain characteristics that relate to the purpose of the decision. Multi criteria have complex structures and have different weights depending upon the consideration of assessors and the purpose of the decision also. Expert’s judgment will be used to detect the criteria weights that applied by assessors. The aim of this study is a model to detect the criteria weights and biases on the subcontractor selection and detecting the significant weights, as decisive criteria. A method, which is used to modeling the weights detection, is the Solver Application. Data, totaling 40 sets, has been collected that consist of the assessor’s assessment and the expert’s judgment. The result is a pattern of weights and biases detection. The proposed model have been able to detect of 20 criteria weights and biases, that consist of 4 criteria in the total weights of 60% (as decisive criteria) and 16 criteria in the total weights of 40%. A model has been built by training process performed by the Solver, which the result for MSE training is 9.73711e-08 and for MSE validation is 0.00900528. Novelty in the study is a model to detect pattern of weights criteria and biases on subcontractor selection by transferring the expert's judgment using Solver Application.