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Fuzzy TOPSIS-Based Group Decision Model for Selecting IT Employees
Abstract
In the era of digitalization, the demand for competent IT employees is growing rapidly. However, the IT employee selection process often faces various challenges, such as biased selection criteria, many applicants, and difficulty in objective assessment. These challenges can lead to inaccurate selection decisions and have a negative impact on company performance. This research aims to develop a Group Decision Support Model (GDSM) for IT Employee Selection using the Fuzzy TOPSIS method to enhance objectivity and reliability in decision-making. This GDSM combines assessments from HRD and User IT groups by considering the weight of each criterion. The proposed model overcomes bias, uncertainty, and subjectivity in judgments from both groups. The GDSM is constructed with 8 parameters/sub-criteria (2 criteria) from the HRD group and 12 parameters (5 criteria) from the User IT group from interviews and research. Thus, the total is 20 assessment parameters, consisting of coding test, education, certification, computer literacy, openness to experience, conscientiousness, extroversion, agreeableness, neuroticism, verbal, numerical, ability to learn, appearance & attitude, work experience, communication skills, time management, job knowledge, motivation to apply, decision making, and service orientation. The methodology involves determining parameters, weights, fuzzification and this GDSM was tested through a limited simulation of IT employee selection using 11 respondents from Computer Science students for evaluation of the model. The result of this model is a ranking of the candidates. The best candidate is Cand. 8, with a closeness coefficient (CC) value of 0.896. The worst candidate is Cand. 3, with CC 0.241. The model is acceptable because it has no difference value between coding and manual for all candidates. This study contributes to increasing objectivity in IT employee selection and offers an implementation model for companies that want to improve the effectiveness of the recruitment process.
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L. Gujuman, L. Sava, S. Sorochin, and T. Mardari, “The specific of IT Recruitment and what is the biggest challenge for an IT Recruiter,” in Proceedings of the 11th International Conference on “Electronics, Communications and Computing (IC|ECCO-2021),” Technical University of Moldova, Apr. 2022, pp. 277–280. doi: 10.52326/ic-ecco.2021/KS.08.
W. I. Safitri and S. Mesran, “Penerapan Metode Preference Selection Index (PSI) Dalam Penerimaan Staff IT,” Bulletin of Informatics and Data Science, vol. 1, no. 1, 2022, [Online]. Available: https://ejurnal.pdsi.or.id/index.php/bids/index
M. G. Aamodt and M. G. Aamodt, Industrial/organizational psychology : an applied approach. Wadsworth, 2010.
Indeed Editorial Team, "IT Requirements and Qualifications (With Careers in IT) | Indeed.com," 11 March 2023. [Online]. Available: https://www.indeed.com/career-advice/career-development/it-jobs-qualification#:~:text=The%20minimum%20degree%20that%20most,Information%20technology%20system%20analysis. [Accessed 8 September 2023].
G. Lewis, "The Most In-Demand Jobs on LinkedIn Right Now," 16 July 2023. [Online]. Available: https://www.linkedin.com/business/talent/blog/talent-strategy/most-in-demand-jobs.
D. deBara, "15 High-Paying Jobs That’ll Be in Demand for Years to Come," 16 February 2023. [Online]. Available: https://www.themuse.com/advice/high-paying-jobs-in-demand-for-future.
M. Shao, Z. Han, J. Sun, C. Xiao, S. Zhang, and Y. Zhao, “A review of multi-criteria decision making applications for renewable energy site selection,” Renew Energy, vol. 157, pp. 377–403, 2020, doi: https://doi.org/10.1016/j.renene.2020.04.137.
H. Q. Nguyen, V. T. Nguyen, D. P. Phan, Q. H. Tran, and N. P. Vu, “Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods,” Applied Sciences (Switzerland), vol. 12, no. 8, Apr. 2022, doi: 10.3390/app12083720.
T. Danişan, E. Özcan, and T. Eren, “Personnel Selection with Multi-Criteria Decision Making Methods in the Ready-to-Wear Sector,” Tehnicki Vjesnik, vol. 29, no. 4, pp. 1339–1347, 2022, doi: 10.17559/TV-20210816220137.
A. Akmaludin, E. G. Sihombing, R. Rinawati, F. Handayanna, L. Sari Dewi, and E. Arisawati, “Generation 4.0 of the programmer selection decision support system: MCDM-AHP and ELECTRE-elimination recommendations,” International Journal of Advances in Applied Sciences, vol. 12, no. 1, p. 48, Mar. 2023, doi: 10.11591/ijaas.v12.i1.pp48-59.
O. Korkmaz, “Personnel Selection Method Based On TOPSIS Multi-Criteria Decision Making Method,” Uluslararası İktisadi ve İdari İncelemeler Dergisi, no. 23, pp. 1–16, Apr. 2019, doi: 10.18092/ulikidince.468486.
D. Priyadharshini, R. Gopinath, and T. S. Poornappriya, “A Fuzzy MCDM Approach for Measuring the Business Impact of Employee Selection,” International Journal of Management (IJM), vol. 11, no. 7, pp. 1769–1775, 2020, doi: 10.34218/IJM.11.7.2020.159.
M. Rabiee, B. Aslani, and J. Rezaei, “A decision support system for detecting and handling biased decision-makers in multi criteria group decision-making problems,” Expert Syst Appl, vol. 171, p. 114597, 2021, doi: https://doi.org/10.1016/j.eswa.2021.114597.
M. M. I. Rahi, A. K. M. A. Ullah, and D. M. G. R. Alam, “A Decision Support System (DSS) for Interview-Based Personnel Selection Using Fuzzy TOPSIS Method,” in Lecture Notes in Networks and Systems, Springer Science and Business Media Deutschland GmbH, 2022, pp. 645–657. doi: 10.1007/978-981-19-2445-3_45.
F. Mar’i, W. F. Mahmudy, and C. Yusainy, “Sistem Rekomendasi Profesi Berdasarkan Dimensi Big Five Personality Menggunakan Fuzzy Inference System Tsukamoto,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 6, no. 5, p. 457, Oct. 2019, doi: 10.25126/jtiik.201965942.
S. W. Chisale and H. S. Lee, “Evaluation of barriers and solutions to renewable energy acceleration in Malawi, Africa, using AHP and fuzzy TOPSIS approach,” Energy for Sustainable Development, vol. 76, Oct. 2023, doi: 10.1016/j.esd.2023.101272.
A. J. Rindengan and Y. A. Langi, Sistem Fuzzy, Bandung: CV. PATRA MEDIA GRAFINDO, 2019.
C. Galve-González, A. B. Bernardo, and A. Castro-López, “Understanding the dynamics of college transitions between courses: Uncertainty associated with the decision to drop out studies among first and second year students,” European Journal of Psychology of Education, 2023, doi: 10.1007/s10212-023-00732-2.
L. H. C. Pinochet, L. M. Onusic, J. C. Z. Costa, M. dos Santos, C. F. S. Gomes, and M. Â. Lellis Moreira, “Design a FUZZY-TOPSIS (FTOPSIS) Model in Decision-Making with Multiple Criteria for the Implementation of Telecommuting in a Public Higher Education Institute,” Procedia Comput Sci, vol. 221, pp. 426–433, 2023, doi: 10.1016/j.procs.2023.07.057.
TRUITY, "Big Five Personality Test," TRUITY, 2024. [Online]. Available: https://www.truity.com/test/big-five-personality-test.
Nuraini, “Analysis of decision support using Elimination and Choice Expressing Reality (ELECTRE) method in determining best candidate for Programmer position,” in Procedia Computer Science, Elsevier B.V., 2022, pp. 571–579. doi: 10.1016/j.procs.2022.12.171.
U. Tanveer, M. D. Kremantzis, N. Roussinos, S. Ishaq, L. S. Kyrgiakos, and G. Vlontzos, “A fuzzy TOPSIS model for selecting digital technologies in circular supply chains,” Supply Chain Analytics, vol. 4, p. 100038, Dec. 2023, doi: 10.1016/j.sca.2023.100038
DOI: https://doi.org/10.47738/jads.v6i1.511
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