Khabib Mustofa

Work place: Department of Computer Science and Electronics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta, Indonesia



Research Interests: Computational Science and Engineering, Computational Engineering, Information Systems, Database Management System


Khabib Mustofa is a lecturer and a researchers at Department of Computer Science and Electronics in Universitas Gadjah Mada, Indonesia. He obtained his bachelor degree of Computer Science in Universitas Gadjah Mada, Indonesia (1997) and Master of Computer Science from Universitas Gadjah Mada (2001) and received Ph.D. from Vienna University of Technology, Austria (2007). His research interests include database system, semantic web, web engineering and information management.


Author Articles
A Method of Weight Update in Group Decision-Making to Accommodate the Interests of All the Decision Makers

By Hamdani Hamdani Retantyo Wardoyo Khabib Mustofa

DOI:, Pub. Date: 8 Aug. 2017

The weight updates are required for group decision-making which has similar parameters used by the decision maker (DM). Each DM as the stakeholder may have similar or different parameters in selecting parameters. Therefore, we have to accommodate the interests of all decision makers (DMs) to obtain alternative decisions. DM who has selected the parameters inputs the initial weight (W_Pi) based on the classical methods, and then recalculates to obtain the updated weights (W_j) until the final weight (W_j^i) is obtained for the alternative of group decision-making (GDM). The initial weight uses a weighting directly or multi criteria decision-making (MCDM). This method aims to provide the fairness for all DMs who have different knowledge in determining the value of the weights and the selection parameters. In order to obtain alternative decisions, we used technique for order preference by similarity to ideal solution (TOPSIS) method to update weight. In this paper, the alternative output of the decisions is applied in two stages: the decisions of each DM and the group, where this output consists of four types of alternatives. Based on the proposed method, the result of GDM shows that the third alternative is recommended in decision-making. This method is effectively performed in decision-making which has different parameters and weights of each DM to support group decision.

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