A Hybrid SITDE Weighting and HYBSO Method in Decision Support Systems for Warehouse Employee Selection

  • Tri Widodo (Corresponding Author) Universitas Teknokrat Indonesia
  • Okma Arnilia Universitas Islam Negeri Siber Syekh Nurjati Cirebon
  • Iryanto Chandra Universitas Islam Negeri Sunan Kalijaga
  • Sahrial Ihsani Ishak Universitas Dian Nusantara
  • Setiawansyah Setiawansyah Universitas Teknokrat Indonesia
Keywords: Warehouse Employee Selection, Heterogeneous Criteria, SITDE, HYBSO, Sensitivity Analysis

Abstract

Warehouse employee selection is a complex process because it involves various heterogeneous criteria, both quantitative and qualitative, such as physical tests, accuracy, work experience, discipline, and teamwork ability. A selection process that still relies on subjective judgment risks producing inconsistent and suboptimal decisions. This study proposes a hybrid method that integrates skewness impact through distributional evaluation (SITDE) for objective determination of criteria weights with a hybrid solution algorithm (HYBSO) for systematic ranking of alternatives. The results of applying this method indicate that Work Experience has the highest weight of 0.2813, followed by the Discipline Test (0.1969) and Physical Test (0.1926), while the Accuracy Test (0.1641) and Teamwork Test (0.1652) have lower weights. The final ranking results show that Candidate HW ranks first with a score of 0.3596, followed by Candidate FN (0.7066) and Candidate DK (0.9162). The sensitivity analysis evaluates the stability of the ranking results under changes in criterion weights across 20 scenarios, demonstrating the robustness of the proposed SITDE-HYBSO method and identifying candidates whose ranking positions are more sensitive to variations in criterion importance. These findings confirm that the SITDE-HYBSO hybrid method is capable of producing objective, consistent, and accountable employee selection decisions, while also providing an adaptive mechanism to respond to changes in organizational priorities.

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References

N. Batarlienė and A. Jarašūnienė, “Improving the Quality of Warehousing Processes in the Context of the Logistics Sector,” Sustainability, vol. 16, no. 6. p. 2595, 2024. doi: 10.3390/su16062595.

B. Y. Ekren, U. Venkatadri, F. Sgarbossa, and E. H. Grosse, “Warehousing 5.0 for the future of the logistics industry,” Int. J. Prod. Res., vol. 64, no. 5, pp. 1587–1597, Mar. 2026, doi: 10.1080/00207543.2026.2617791.

J. Li, R. He, and T. Wang, “A data-driven decision-making framework for personnel selection based on LGBWM and IFNs,” Appl. Soft Comput., vol. 126, p. 109227, 2022, doi: https://doi.org/10.1016/j.asoc.2022.109227.

Afolabi Ogbeyemi, Akinola Ogbeyemi, and Wenjun Zhang, “Integrating human factors into the distribution model of goods and fast-moving consumer goods for effective inventory control,” Int. J. Eng. Bus. Manag., vol. 16, p. 18479790241266350, May 2024, doi: 10.1177/18479790241266352.

M. A. Rahman and E. D. Kirby, “The Lean Advantage: Transforming E-Commerce Warehouse Operations for Competitive Success,” Logistics, vol. 8, no. 4. p. 129, 2024. doi: 10.3390/logistics8040129.

S. Jahangir, R. Xie, A. Iqbal, and M. Hussain, “The Influence of Sustainable Human Resource Management Practices on Logistics Agility: The Mediating Role of Artificial Intelligence,” Sustainability, vol. 17, no. 7. p. 3099, 2025. doi: 10.3390/su17073099.

T. De Lombaert, K. Braekers, R. De Koster, S. Lizin, and K. Ramaekers, “Eliciting and integrating order picker preferences in the evaluation of job assignment mechanisms in warehousing,” Comput. Ind. Eng., vol. 211, p. 111613, 2026, doi: https://doi.org/10.1016/j.cie.2025.111613.

Ziyao Li and Xiaobo Jia, “Analysis of Logistics Curriculum and Recruitment Requirements Based on Text Mining: A Case Study of China,” Sage Open, vol. 14, no. 2, p. 21582440241239840, Apr. 2024, doi: 10.1177/21582440241239839.

Trung-Hieu Nguyen, “Research on Factors Influencing the Employees’ Digital Transformation Engagement and Job Performance in Logistics Companies,” Sage Open, vol. 15, no. 3, p. 21582440251353390, Jul. 2025, doi: 10.1177/21582440251353391.

A. R. Mishra, P. Rani, F. Cavallaro, I. M. Hezam, and J. Lakshmi, “An Integrated Intuitionistic Fuzzy Closeness Coefficient-Based OCRA Method for Sustainable Urban Transportation Options Selection,” Axioms, vol. 12, no. 2, p. 144, Jan. 2023, doi: 10.3390/axioms12020144.

K. Kara, E. Akagün Ergin, G. Cihan Yalçın, T. Çelik, M. Deveci, and S. Kadry, “Sustainable brand logo selection using an AI-Supported PF-WENSLO-ARLON hybrid method,” Expert Syst. Appl., vol. 260, p. 125382, 2025, doi: https://doi.org/10.1016/j.eswa.2024.125382.

D. Pamucar, V. Simic, Ö. F. Görçün, and H. Küçükönder, “Selection of the best Big Data platform using COBRAC-ARTASI methodology with adaptive standardized intervals,” Expert Syst. Appl., vol. 239, p. 122312, 2024, doi: https://doi.org/10.1016/j.eswa.2023.122312.

S. M. Durmuşoğlu and Ö. Atlam, “A methodological framework for evaluating thermal fluids in solar power applications via the simple additive weighting technique,” J. Therm. Anal. Calorim., 2026, doi: 10.1007/s10973-025-15276-4.

A. Keshtpour and R. K. Chakrabortty, “The selection of saltwater desalination technology using new measurement alternatives by a combination of angle and distance (MACAD) method: a case study,” Environ. Syst. Decis., vol. 45, no. 3, p. 41, 2025, doi: 10.1007/s10669-025-10034-1.

Y. B. Gopisetty and H. R. Sama, “Skewness impact through distributional evaluation (SITDE) method: a new method in multi-criteria decision making,” J. Oper. Res. Soc., vol. 76, no. 6, pp. 1204–1224, Jun. 2025, doi: 10.1080/01605682.2024.2416910.

L. K. V, S. Kamruddin, V. K. K.S, S. Kalvakolanu, V. Nalluri, and J.-R. Chang, “A Multi-Criteria Decision-Making Approach to Improve Criteria Ranking and Weighting: Integrating SITDE Weighting With PIV and RAM Techniques,” Asian J. Interdiscip. Res., vol. 8, no. 2 SE-Articles, pp. 1–20, Apr. 2025, doi: 10.54392/ajir2521.

Y. Djeddi, “Hybrid Solution (HYBSO) based on Hybrids Normalization and Aggregation for the Multi-criteria Decision-Making Problems,” Yugosl. J. Oper. Res., vol. 36, no. 1, pp. 1–24, 2026, doi: 10.2298/YJOR241020020D.

F. Mizrak, K. C. Mizrak, and G. R. Akkartal, “Developing a strategic framework for airline destination selection: A multi-criteria decision-making approach applied to Turkish airlines,” Transp. Res. Interdiscip. Perspect., vol. 29, p. 101322, 2025, doi: https://doi.org/10.1016/j.trip.2025.101322.

I. Tronnebati, F. Jawab, Y. Frichi, and J. Arif, “Green Supplier Selection Using Fuzzy AHP, Fuzzy TOSIS, and Fuzzy WASPAS: A Case Study of the Moroccan Automotive Industry,” Sustainability, vol. 16, no. 11. 2024. doi: 10.3390/su16114580.

M. A. Hatefi, “A new method for weighting decision making attributes: an application in high-tech selection in oil and gas industry,” Soft Comput., vol. 28, no. 1, pp. 281–303, 2024, doi: 10.1007/s00500-023-09282-7.

S. Ashraf, W. Iqbal, M. S. Hameed, V. Simic, and N. Bacanin, “An enhanced CRADIS decision model for optimizing radioactive waste reduction through transmutations based on Disc Spherical Fuzzy information,” Appl. Soft Comput., vol. 167, p. 112289, 2024, doi: https://doi.org/10.1016/j.asoc.2024.112289.

T. Van Dua, “A Novel Approach for Criteria Weight Determination: A Case Study in Machine Ranking,” Eng. Technol. Appl. Sci. Res., vol. 16, no. 1 SE-, pp. 31333–31337, Feb. 2026, doi: 10.48084/etasr.15778.

A. Biswas, K. H. Gazi, P. M. Sankar, and A. Ghosh, “A Decision-Making Framework for Sustainable Highway Restaurant Site Selection: AHP-TOPSIS Approach based on the Fuzzy Numbers,” Spectr. Oper. Res., vol. 2, no. 1 SE-Articles, pp. 1–26, Jan. 2025, doi: 10.31181/sor2120256.

E. Carnia et al., “An Integrated Weighted Fuzzy N-Soft Set–CODAS Framework for Decision-Making in Circular Economy-Based Waste Management Supporting the Blue Economy: A Case Study of the Citarum River Basin, Indonesia,” Mathematics, vol. 14, no. 2. p. 238, 2026. doi: 10.3390/math14020238.

S. S. Yildiz, “Spatial multi-criteria decision making approach for wind farm site selection: A case study in Balıkesir, Turkey,” Renew. Sustain. Energy Rev., vol. 192, p. 114158, 2024, doi: https://doi.org/10.1016/j.rser.2023.114158.

Published
2026-09-21
How to Cite
Widodo, T., Arnilia, O., Chandra, I., Ishak, S. I., & Setiawansyah, S. (2026). A Hybrid SITDE Weighting and HYBSO Method in Decision Support Systems for Warehouse Employee Selection. Journal of Artificial Intelligence and Technology Information (JAITI), 4(3), 593-611. https://doi.org/10.58602/jaiti.v4i3.344