Integrated MCDM-AHP and MABAC for Selection Head of Branch Offices
DOI:
10.33395/sinkron.v8i4.13669Keywords:
Bracnd head offices, Integrated, MABAC, MCDM-AHP, Multi-criteria.Abstract
Leadership changes are very urgent in maintaining organizational stability. A good relay can build significant strength in carrying out organizational operational activities, of course this must be done with good selection. The purpose of this writing is to provide a consistent picture of the selection of branch heads in carrying out business competition which is measured based on the competencies possessed by the selected employees. The barometer is determined based on eight criteria as an assessment that is declared objective by the leadership, namely critical thinking, communication, analyzing, creative and innovation, leadership, adaptation, cooperation, and public speaking. The method used will be implemented in an integrated manner from the two MCDM-AHP methods and the MABAC method. These two methods have similar applications to the selection process. MCDM-AHP is used to select eight criteria as determinants of weighting and the MABAC method is used to determine the ranking process assessment for integrated decision making. The results obtained based on the weighted matrices of the branch head office selection process were measurably obtained, namely that the first priority was held by A11 with a weight of 1,406. The results of the integrity of both methods can provide evidence of decision support for the branch head selection process consistently with optimal results. The ranking system can be regulated and utilized for the purposes of selecting leaders to be placed in other positions.
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Akmaludin, A., Sihombing, E. G., Rinawati, R., Handayanna, F., Sari Dewi, L., & Arisawati, E. (2023). Generation 4.0 of the programmer selection decision support system: MCDM-AHP and ELECTRE-elimination recommendations. International Journal of Advances in Applied Sciences, 12(1), 48. https://doi.org/10.11591/ijaas.v12.i1.pp48-59
Akmaludin, Samudi, Palasara, N., Harmono, F. P., Widianto, K., & Muharrom, M. (2023). MCDM-AHP and PROMETHEE methods integrated for base service strategy vendor evaluation and selection. International Journal of Advances in Applied Sciences, 12(4), 384–395. https://doi.org/10.11591/ijaas.v12.i4.pp384-395
Ampofo, S., Issifu, J. S., Kusibu, M. M., Mohammed, A. S., & Adiali, F. (2023). Selection of the final solid waste disposal site in the Bolgatanga municipality of Ghana using analytical hierarchy process (AHP) and multi-criteria evaluation (MCE). Heliyon, 9(8), e18558. https://doi.org/10.1016/j.heliyon.2023.e18558
Bhat, A. A., Mir, A. A., Allie, A. H., Ahmad Lone, M., Al-Adwan, A. S., Jamali, D., & Riyaz, I. (2024). Unlocking corporate social responsibility and environmental performance: Mediating role of green strategy, innovation, and leadership. Innovation and Green Development, 3(2), 100112. https://doi.org/10.1016/j.igd.2023.100112
Bid, S., & Siddique, G. (2019). Human risk assessment of Panchet Dam in India using TOPSIS and WASPAS Multi-Criteria Decision-Making (MCDM) methods. Heliyon, 5(6), e01956. https://doi.org/10.1016/j.heliyon.2019.e01956
Büscher, S., & Bauer, D. (2023). Weighting Strategies for Pairwise Composite Marginal Likelihood Estimation in Case of Unbalanced Panels and Unaccounted Autoregressive Structure of the Errors. Available at SSRN 4385804, 181(October 2023), 1–34. https://doi.org/10.1016/j.trb.2024.102890
Chakraborty, S., Raut, R. D., Rofin, T. M., Chatterjee, S., & Chakraborty, S. (2023). A comparative analysis of Multi-Attributive Border Approximation Area Comparison (MABAC) model for healthcare supplier selection in fuzzy environments. Decision Analytics Journal, 8(July), 100290. https://doi.org/10.1016/j.dajour.2023.100290
Demir, A. S., Yazici, E., Oğur, Y. S., & Yazici, A. B. (2023). Analysis of the performance of assessment scales with multi-criteria decision-making techniques. Journal of Engineering Research (Kuwait), 11(3), 192–197. https://doi.org/10.1016/j.jer.2023.100087
Deretarla, Ö., Erdebilli, B., & Gündoğan, M. (2023). An integrated Analytic Hierarchy Process and Complex Proportional Assessment for vendor selection in supply chain management. Decision Analytics Journal, 6(August 2022), 100155. https://doi.org/10.1016/j.dajour.2022.100155
Ekström, S. E., Garoni, C., Jozefiak, A., & Perla, J. (2021). Eigenvalues and eigenvectors of tau matrices with applications to Markov processes and economics. In Linear Algebra and Its Applications (Vol. 627). Elsevier Inc. https://doi.org/10.1016/j.laa.2021.06.005
Elshall, A., Ye, M., Kranz, S. A., Harrington, J., Yang, X., Wan, Y., & Maltrud, M. (2022). Application-specific optimal model weighting of global climate models: A red tide example. Climate Services, 28(August), 100334. https://doi.org/10.1016/j.cliser.2022.100334
Erzan, A., & Tuncer, A. (2020). Explicit construction of the eigenvectors and eigenvalues of the graph Laplacian on the Cayley tree. Linear Algebra and Its Applications, 586, 111–129. https://doi.org/10.1016/j.laa.2019.10.023
Goswami, S. S., & Mitra, S. (2020). Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology. International Journal of Data and Network Science, 4(1), 27–42. https://doi.org/10.5267/j.ijdns.2019.8.004
Hema Surya, S., Nirmala, T., & Ganesan, K. (2023). Interval linear algebra – A new perspective. Journal of King Saud University - Science, 35(2), 102502. https://doi.org/10.1016/j.jksus.2022.102502
Moslem, S., & Pilla, F. (2024). Planning location of parcel lockers using group Analytic Hierarchy Process in Spherical Fuzzy environment. Transportation Research Interdisciplinary Perspectives, 24(October 2023), 101024. https://doi.org/10.1016/j.trip.2024.101024
Olabanji, O. M., & Mpofu, K. (2014). Comparison of weighted decision matrix, and analytical hierarchy process for CAD design of reconfigurable assembly fixture. Procedia CIRP, 23(C), 264–269. https://doi.org/10.1016/j.procir.2014.10.088
Rudnik, K., Bocewicz, G., Kucińska-Landwójtowicz, A., & Czabak-Górska, I. D. (2021). Ordered fuzzy WASPAS method for selection of improvement projects. Expert Systems with Applications, 169. https://doi.org/10.1016/j.eswa.2020.114471
Shanta, M. H., Choudhury, I. A., & Salman, S. (2024). Municipal solid waste management: Identification and analysis of technology selection criteria using Fuzzy Delphi and Fuzzy DEMATEL technique. Heliyon, 10(1), e23236. https://doi.org/10.1016/j.heliyon.2023.e23236
Shpiz, G. B., Litvinov, G. L., & Sergeev, S. N. (2013). On common eigenvectors for semigroups of matrices in tropical and traditional linear algebra. Linear Algebra and Its Applications, 439(6), 1651–1656. https://doi.org/10.1016/j.laa.2013.04.036
Tang, B., Han, Y., He, G., & Li, X. (2024). The chain mediating effect of shared leadership on team innovation. Heliyon, 10(3), e25282. https://doi.org/10.1016/j.heliyon.2024.e25282
Waas, D. V., Sudipa, I. G. I., Agus, I. P., & Darma, E. (2022). Comparison of Final Results Using Combination AHP-VIKOR And AHP-SAW Methods In Performance Assessment ( Case Imanuel Lurang Congregation ). International Journal of Information & Technology, 5(158), 612–623.
Wang, J., Wei, G., Wei, C., & Wei, Y. (2020). MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment. Defence Technology, 16(1), 208–216. https://doi.org/10.1016/j.dt.2019.06.019
Yang, D., Song, D., & Li, C. (2022). Environmental responsibility decisions of a supply chain under different channel leaderships. Environmental Technology and Innovation, 26, 102212. https://doi.org/10.1016/j.eti.2021.102212
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Copyright (c) 2024 Akmaludin, Adhi Dharma Suriyanto, Nandang Iriadi, Kudiantoro Widianto
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