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The Weights Detection of Multi-criteria by using Solver

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 7 No. 2 (2017)

DOI
10.11591/ijece.v7i2.pp858-868
ISSN
2088-8708, 2088-8708
Published
2017-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

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.

Collaboration network of the authors

10 authors · 17 co-authorship links

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  • Universitas Syiah Kuala
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Fitri ArniaUniversitas Syiah Kuala2
Khairun SaddamiUniversitas Syiah Kuala2
Khairul MunadiUniversitas Syiah Kuala2
Abdullah AbdullahUniversitas Syiah Kuala2
Teuku Budi AuliaUniversitas Syiah Kuala2
Zulfikar ZulfikarUniversitas Syiah Kuala1
Rafiqa Shahnaz NoorUniversitas Syiah Kuala1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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