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Group Decision Support System Using SMART-COPELAND SCORE Model In Choosing The Best Alternative Pair
Abstract
Purpose: Adjust the Group Decision Support System (GDSS) model in completing case studies of selecting the best alternative candidate pairs for the OSIS core board with many decision-makers and problems in the differences in the preferences of decision-makers as well as modeling in decision making with multi-criteria and multi-attributes and combining preferences decision-makers to choose the best alternative partner candidate.
Design/methodology/approach: The Group Decision Support System (GDSS) model combines the SMART method for modeling multi-criteria and multi-attribute assessments and the Copeland Score model for aggregating the judgments of five decision-makers against the selected pair of OSIS core board candidates using a voting mechanism.
Findings/result: The comparison test for the manual calculation of the SMART- Copeland Score Model method with the results of the system calculation is the same. From the ten alternative data in the first stage of the test through the SMART method calculation, it then passes into four alternatives divided into two alternative candidate pairs, namely alternative candidate pairs (A1, A3) and alternative candidate pairs (A2, A4). The second stage test uses calculations Copeland Score voting, which produces the best alternative candidate pair, namely alternative (A1, A3) with a final point score = 4.
Originality/value/state of the art: Based on a review of previous research, this study uses line-up criteria, written tests, and interview tests with the SMART method to calculate alternative scores on each criteria, and the Copeland Score model to aggregate decision makers' preferences to produce the best alternative candidate pairs. In calculating the final value of the alternative ranking.Keywords
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E. Triantaphyllou, B. Shu, S. N. Sanchez, and T. Ray, “Multi-Criteria Decision Making : An Operations Research Approach,” Electronics, vol. 15, pp. 175–186, 1998.
C. Hwang and K. Yoon, Multiple Attribute Decision Making: Methods and Applications, A State of the Art Survey. 1981. doi: 10.1007/978-3-642-48318-9.
M. Reisi, A. Afzali, and L. Aye, “Applications of analytical hierarchy process (AHP) and analytical network process (ANP) for industrial site selections in Isfahan, Iran,” Environ. Earth Sci., 2018, doi: 10.1007/s12665-018-7702-1.
A. Mardani et al., “A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015,” Renewable and Sustainable Energy Reviews. 2017. doi: 10.1016/j.rser.2016.12.053.
B. Gavish and J. H. Gerdes, “Voting mechanisms and their implications in a GDSS environment,” Ann. Oper. Res., vol. 71, pp. 41–74, 1997.
S. P. Nugroho, “Development of a Group Decision Support System with the Multi-Stage Multi-Attribute Group Decision Making (MS-MAGDM) Method on the Intelligent Warehouse Management System,” Telemat. J. Inform. dan Teknol. Inf., vol. 18, no. 2, pp. 231–243, 2021.
I. M. D. P. Asana, I. G. I. Sudipa, and K. A. P. Putra, “A Decision Support System on Employee Assessment Using Analytical Network Process (ANP) and BARS Methods,” J. Tek. Inform. CIT Medicom, vol. 13, no. 1, pp. 1–12, 2021.
I. N. T. A. Putra, K. S. Kartini, N. K. A. Sinariyani, and N. Maharani, “Decision Support System For Determining The Type Of Workout Using The Fuzzy Analythical Hierarchy Process (F-AHP) In GYM STIKI,” Telemat. J. Inform. dan Teknol. Inf., vol. 18, no. 1, pp. 73–87, 2021.
A. Alinezhad and J. Khalili, New methods and applications in multiple attribute decision making (MADM), vol. 277. Springer, 2019.
V. A. Permadi, R. P. Agusdin, S. P. Tahalea, and W. Kaswidjanti, “Identification of Student Area of Interest using Fuzzy Multi-Attribute Decision Making (FMADM) and Simple Additive Weighting (SAW) Methods (Case Study: Information System Major, Universitas Pembangunan Nasional" Veteran" Yogyakarta),” in Proceeding of LPPM UPN “Veteran” Yogyakarta Conference Series 2020–Engineering and Science Series, 2020, vol. 1, no. 1, pp. 420–428.
W. Setiawan, N. Pranoto, and K. Huda, “Employee Performance Evaluation Decision Support System with the SMART (Simple Multi-Attribute Rating Technique) Method,” J. RESTI (Rekayasa Sist. Dan Teknol. Informasi), vol. 4, no. 1, pp. 50–55, 2020.
S. Nanayakkara, M. N. N. Rodrigo, S. Perera, G. T. Weerasuriya, and A. A. Hijazi, “A methodology for selection of a Blockchain platform to develop an enterprise system,” J. Ind. Inf. Integr., vol. 23, p. 100215, 2021.
D. Siregar, D. Arisandi, A. Usman, D. Irwan, and R. Rahim, “Research of simple multi-attribute rating technique for decision support,” in Journal of Physics: Conference Series, 2017, vol. 930, no. 1, p. 12015.
F. M. Kasie, “Combining Simple Multiple Attribute Rating Technique and Analytical Hierarchy Process for Designing Multi-Criteria Performance Measurement Framework,” Glob. J. Res. Eng. Ind. Eng., vol. 13, no. 1, pp. 15–30, 2013.
Y. Chen, G. E. Okudan, and D. R. Riley, “Decision support for construction method selection in concrete buildings: Prefabrication adoption and optimization,” Autom. Constr., vol. 19, no. 6, pp. 665–675, 2010.
P. Sugiartawan, S. Hartati, and A. Musdholifah, “Modeling of a tourism group decision support system using risk analysis based knowledge base,” Int. J. Adv. Comput. Sci. Appl, vol. 11, no. 7, pp. 354–363, 2020.
H. Setiawan, J. E. Istiyanto, R. Wardoyo, and P. Santoso, “The Group Decision Support System to Evaluate the ICT Project Performance Using the Hybrid Method of AHP, TOPSIS and Copeland Score,” Int. J. Adv. Comput. Sci. Appl., vol. 7, no. 4, 2016.
S. Hartati, R. Wardoyo, and A. Harjoko, “Development of copeland score methods for determine group decisions,” Int. J. Adv. Comput. Sci. Appl., vol. 4, no. 6, 2013.
A. P. Sahida, B. Surarso, and R. Gernowo, “The combination of the MOORA method and the Copeland Score method as a Group Decision Support System (GDSS) Vendor Selection,” in 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2019, pp. 340–345.
P. Sugiartawan and S. Hartati, “Group Decision Support System to Selection Tourism Object in Bali Using Analytic Hierarchy Process (AHP) and Copeland Score Model,” in 2018 Third International Conference on Informatics and Computing (ICIC), 2018, pp. 1–6.
J. W. Weiss, D. J. Weiss, J. W. Weiss, and D. J. Weiss, “SMARTS and SMARTER: Improved Simple Methods for Multiattribute Utility Measurement,” A Science of Decision Making. pp. 409–421, 2009. doi: 10.1093/acprof:oso/9780195322989.003.0031.
F. M. Kasie, “Combining simple multiple attribute rating technique and analytical hierarchy process for designing multi-criteria performance measurement framework,” Glob. J. Res. Eng., 2013.
M. Soroudi, G. Omrani, F. Moataar, and S. A. Jozi, “Modelling an Integrated Fuzzy Logic and Multi-Criteria Approach for Land Capability Assessment for Optimized Municipal Solid Waste Landfill Siting Yeast.,” Polish J. Environ. Stud., vol. 27, no. 1, 2018.
DOI: https://doi.org/10.31315/telematika.v19i1.7181
DOI (PDF): https://doi.org/10.31315/telematika.v19i1.7181.g4430
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Status Kunjungan Jurnal Telematika