Work place: Department of Computer Science, Faculty of Computer Science and Information Technology, Universitas Mulawarman, Samarinda, Indonesia
E-mail: hamdani@fkti.unmul.ac.id
Website:
Research Interests: Medical Informatics, Computer systems and computational processes, Computer Vision, Operating Systems, Systems Architecture
Biography
H. Hamdani is a lecturer and a researchers at Department of Computer Science in Universitas Mulawarman, Indonesia. He obtained his bachelor degree of Informatics in Universitas Ahmad Dahlan, Indonesia (2002). He obtained his Master of Computer Science in Universitas Gadjah Mada, Indonesia (2009) and candidate his Ph.D program in Computer Science at Department of Computer Science & Electronics in Universitas Gadjah Mada, Yogyakarta, Indonesia. His research interests include decision support systems (DSS), group decision support systems (GDSS), social networks analysis, intelligent system, information security and web engineering.
E-mail: hamdani@fkti.unmul.ac.id / danifn@mail.ugm.ac.id
By Noor Alam Hadiwijaya Hamdani Hamdani Andri Syafrianto Zaidir Tanjung
DOI: https://doi.org/10.5815/ijisa.2018.09.03, Pub. Date: 8 Sep. 2018
The criteria and sub criteria-based decision model for selection of tourism site using Analytic Network Process (ANP) method was to be implemented in Yogyakarta, Indonesia. In this study, we proposed criteria and sub criteria that influenced each other and had feedback between the two so that there was a comparison of tourism site alternatives according to sub criteria and pairwise comparative assessment with scale 1-9 that was then calculated in form of matrix of pairwise comparison. The result of this study was in form of decision alternatives in form of ranking to facilitate decision makers (DMs) in finding tourism sites.
[...] Read more.By Hamdani Hamdani Retantyo Wardoyo Khabib Mustofa
DOI: https://doi.org/10.5815/ijisa.2017.08.01, 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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