Combination of Rank Sum and Multi Attribute Utility Theory in Determining the Best Receptionist Performance
DOI:
https://doi.org/10.30865/klik.v4i5.1791Keywords:
Best Cashier; MAUT; Performance; Rank Sum; Weighting MethodAbstract
As the frontline of the service industry, a receptionist's performance not only reflects his professionalism, but also affects the first impression and overall customer experience. Problems in assessing the performance of a receptionist can include several things, namely difficulty measuring the quality of social interactions objectively, performance appraisals often focus more on administrative tasks, lack of understanding of the receptionist's role as a liaison between the company and customers, difficulty in assessing intangible aspects such as friendliness, patience, or the ability to respond to changing customer needs quickly and efficiently. The combination of rank sum weighting methods and Multi-Attribute Utility Theory (MAUT) can result in a more holistic and robust approach to decision making. In this approach, the rank sum weighting method can be used to get an initial picture of the relative preferences of various alternatives, while MAUT can be used to dig deeper into those preferences and account for complex factors such as attribute weights and utility values. By combining these two methods, decision makers can gain a deeper understanding of their preferences, while still maintaining openness to multiple perspectives and information. The results of the ranking of the best cashier performance the 1st best cashier with a value of 0.574 obtained by Zulaikah, the 2nd best cashier with a value of 0.473 obtained by Arini, and the 3rd best cashier with a value of 0.337 obtained by Lilik Karlina.
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T. Suwarto, C. Pforr, and M. Volgger, “Front-desk workforce cultural diversity and its implications for service quality in the accommodation sector: a case from Australia,” Tour. Rev., vol. 79, no. 1, pp. 234–249, 2024.
W. Saputra, S. A. Wardana, H. Wahyuda, and D. A. Megawaty, “Penerapan Kombinasi Metode Multi-Attribute Utility Theory (MAUT) dan Rank Sum Dalam Pemilihan Siswa Terbaik,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 2, no. 1, pp. 12–21, 2024.
M. I. Fikri, E. Haerani, I. Afrianty, and S. Ramadhani, “Sistem Pendukung Keputusan Penilaian Kinerja Guru Menggunakan Metode Multi Attribute Utility Theory (MAUT),” JURIKOM (Jurnal Ris. Komputer), vol. 9, no. 5, pp. 1271–1280, 2022.
J. H. Lubis, S. Esabella, M. Mesran, D. Desyanti, and D. M. Simanjuntak, “Penerapan Metode Multi Attribute Utility Theory (MAUT) Dalam Pemilihan Karyawan yang di Non-Aktifkan di Masa Pandemi,” J. Media Inform. Budidarma, vol. 6, no. 2, pp. 969–978, 2022.
F. El Khair, S. Defit, and Y. Yuhandri, “Sistem Keputusan dengan Metode Multi Attribute Utility Theory dalam Penilaian Kinerja Pegawai,” J. Inf. dan Teknol., pp. 215–220, 2021.
M. Kayac?k, H. Dinçer, and S. Yüksel, “Using quantum spherical fuzzy decision support system as a novel sustainability index approach for analyzing industries listed in the stock exchange,” Borsa Istanbul Rev., vol. 22, no. 6, pp. 1145–1157, 2022.
N. Panigrahi, I. Ayus, and O. P. Jena, “An expert system?based clinical decision support system for Hepatitis?B prediction & diagnosis,” Mach. Learn. Healthc. Appl., pp. 57–75, 2021.
H. Sulistiani, Setiawansyah, P. Palupiningsih, F. Hamidy, P. L. Sari, and Y. Khairunnisa, “Employee Performance Evaluation Using Multi-Attribute Utility Theory (MAUT) with PIPRECIA-S Weighting: A Case Study in Education Institution,” in 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS), 2023, pp. 369–373. doi: 10.1109/ICIMCIS60089.2023.10349017.
Setiawansyah, A. A. Aldino, P. Palupiningsih, G. F. Laxmi, E. D. Mega, and I. Septiana, “Determining Best Graduates Using TOPSIS with Surrogate Weighting Procedures Approach,” in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), 2023, pp. 60–64. doi: 10.1109/IConNECT56593.2023.10327119.
Z. M. Arini, D. J. Sitanggang, M. Ali, and S. Aripin, “Sistem Pendukung Keputusan Penentuan Facial Wash Terbaik yang digunakan pada kulit berminyak dengan menggunakan Metode Multi Attribute Utility Theory (MAUT) dan Pembobotan Rank Order Centroid (ROC),” in Prosiding Seminar Nasional Sosial, Humaniora, dan Teknologi, 2022, pp. 317–324.
A. A. Kusuma, Z. M. Arini, U. Hasanah, M. Mesran, and M. Kom, “Analisa Penerapan Metode Multi Attribute Utility Theory (MAUT) dengan Pembobotan Rank Order Centroid (ROC) Dalam Pemilihan Lokasi Strategis Coffeshop Milenial di Era New Normal,” J. Sist. Komput. dan Inform., vol. 3, no. 2, pp. 51–59, 2021.
V. R. Campos and D. J. S. Moreira, “Risk assessment with multi-attribute utility theory for building projects,” J. Build. Pathol. Rehabil., vol. 7, no. 1, p. 98, 2022.
H. Jaafaru and B. Agbelie, “Bridge maintenance planning framework using machine learning, multi-attribute utility theory and evolutionary optimization models,” Autom. Constr., vol. 141, p. 104460, 2022.
A. F. O. Pasaribu, “Decision Support System for Best Supplier Selection Using Simple Additive Weighting and Rank Sum Weighting,” Chain J. Comput. Technol. Comput. Eng. Informatics, vol. 1, no. 3, pp. 106–112, 2023.
P. J. Krishna, V. P. Meena, V. P. Singh, and B. Khan, “Rank-sum-weight method based systematic determination of weights for controller tuning for automatic generation control,” IEEE Access, vol. 10, pp. 68161–68174, 2022.
S. Sintaro, “Sistem Pendukung Keputusan Penentuan Barista Terbaik Menggunakan Rank Sum dan Additive Ratio Assessment (ARAS),” J. Ilm. Comput. Sci., vol. 2, no. 1, pp. 39–49, 2023, doi: 10.58602/jics.v2i1.15.
I. M. Hezam, A. K. Mishra, D. Pamucar, P. Rani, and A. R. Mishra, “Standard deviation and rank sum-based MARCOS model under intuitionistic fuzzy information for hospital site selection,” Kybernetes, 2023.
Z. Wang, J. Wang, D. Yu, and K. Chen, “The potential evaluation of groundwater by integrating rank sum ratio (RSR) and machine learning algorithms in the Qaidam Basin,” Environ. Sci. Pollut. Res., vol. 30, no. 23, pp. 63991–64005, 2023.
V. Pradhan, J. Dhar, and A. Kumar, “Software reliability models and multi-attribute utility function based strategic decision for release time optimization,” in Predictive Analytics in System Reliability, Springer, 2022, pp. 175–190.
F. A. AlFaraidy, K. S. Teegala, and G. Dwivedi, “Selection of a Sustainable Structural Floor System for an Office Building Using the Analytic Hierarchy Process and the Multi-Attribute Utility Theory,” Sustainability, vol. 15, no. 17, p. 13087, 2023.
C. Campos Valverde, “Adding value to a mining corporation through project portfolio management: Combined approaches of portfolio theory and multi-attribute utility theory,” 2023.
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