Combination of CRITIC Weighting Method and Multi-Atributive Ideal-Real Comparative Analysis in Staff Admissions

Muhammad Waqas Arshad; Mesran; Setiawansyah Setiawansyah; Ryan Randy Suryono; Yuri Rahmanto

doi:10.47065/explorer.v4i2.1428

Muhammad Waqas Arshad University of Bologna, Italy
Mesran Universitas Budi Darma, Indonesia
Setiawansyah Setiawansyah * Universitas Teknokrat Indonesia, Indonesia
Ryan Randy Suryono Universitas Teknokrat Indonesia, Indonesia
Yuri Rahmanto Universitas Teknokrat Indonesia, Indonesia

DOI: https://doi.org/10.47065/explorer.v4i2.1428

Keywords: Combination; CRITIC Weighting Method; Integration; MAIRCA Method; Staff Recruitment

Abstract

Staff recruitment is a critical process in human resource management where organizations select and place individuals who fit the needs and goals of the company. This process involves identifying position needs, job postings, screening applicants, interviewing, skills evaluation, and making a final decision to determine the most suitable employee. The integration of CRITIC and MAIRCA allows the staff selection process to be more objective and systematic. CRITIC helps in assessing the importance of each criterion by considering its relevance, thus ensuring that the evaluation is not based on just one dimension. On the other hand, MAIRCA provides a comprehensive framework by comparing each candidate against the desired ideal standards and their actual achievements in relevant attributes. The combination of these two methods not only strengthens accuracy in staff selection, but also ensures that decisions are made in accordance with the organization's strategic goals to achieve optimal performance and effectiveness. The ranking results obtained the results of rank 1 with a value of 0.0824 obtained by Alternative G, rank 2 with a value of 0.0798 obtained by Alternative B, and rank 3 with a value of 0.0778 obtained by Alternative C.

References

[1] D. T. Do and N.-T. Nguyen, “Applying Cocoso, Mabac, Mairca, Eamr, Topsis and weight determination methods for multi-criteria decision making in hole turning process,” Strojnícky časopis-Journal Mech. Eng., vol. 72, no. 2, pp. 15–40, 2022.
[2] M. C. J. Anand, K. Kalaiarasi, N. Martin, B. Ranjitha, S. S. Priyadharshini, and M. Tiwari, “Fuzzy C-Means Clustering with MAIRCA-MCDM Method in Classifying Feasible Logistic Suppliers of Electrical Products,” in 2023 First International Conference on Cyber Physical Systems, Power Electronics and Electric Vehicles (ICPEEV), 2023, pp. 1–7.
[3] S. Chakraborty, P. Chatterjee, and P. P. Das, “Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) Method,” in Multi-Criteria Decision-Making Methods in Manufacturing Environments, Apple Academic Press, 2024, pp. 289–296.
[4] D. Handoko, “Multi-Criteria Decision-Making Pemilihan Kostan Menggunakan Multi-Atributive Ideal-Real Comparative Analysis (MAIRCA),” Chain J. Comput. Technol. Comput. Eng. Informatics, vol. 2, no. 1, pp. 1–10, 2024.
[5] D. Pasha and M. Safi, “Penerapan Multi-Atributive Ideal-Real Comparative Analysis dan PIPRECIA Dalam Evaluasi Kinerja Pemasok Bahan Baku,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 4, no. 4, pp. 2005–2017, 2024, doi: 10.30865/klik.v4i4.1652.
[6] Y. Yusman, S. Nadriati, and N. Putra, “Sistem Pendukung Keputusan Seleksi Penerimaan Karyawan Pada Pt Pelindo I Mengunakan Metode Simple Additive Weighting (Saw),” J. Digit Digit. Inf. Technol., vol. 12, no. 1, pp. 12–22, 2022.
[7] C. Rozali, A. Zein, and S. Farizy, “Penerapan Analytic Hierarchy Process (AHP) untuk Pemilihan Penerimaan Karyawan Baru,” J. Inform. Utama, vol. 1, no. 2, pp. 32–36, 2023.
[8] M. N. D. Satria, “Sistem Pendukung Keputusan Penerimaan Staff Administrasi Menggunakan Metode VIKOR,” J. Artif. Intell. Technol. Inf., vol. 1, no. 1, pp. 39–49, 2023.
[9] A. Al Firdaus and J. Sutresna, “SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMAAN KARYAWAN BARU BERBASIS WEB MENGGUNAKAN METODE MABAC,” Sci. J. Ilm. Sains dan Teknol., vol. 2, no. 8, pp. 39–55, 2024.
[10] M. Hidayatullah and A. Ikhwan, “Implementasi Metode Rank Order Centroid Dan Multi Attributive Border Approximation Area Comparison Dalam Penerimaan Karyawan,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 4, no. 6, pp. 2971–2981, 2024.
[11] 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.
[12] E. R. Susanto, A. Savitri Puspaningrum, and Z. Abidin, “Recommendations of Cash Social Assistance (BST) Recipients for People Affected by Covid-19 Using AHP-TOPSIS,” in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), Aug. 2023, pp. 190–195. doi: 10.1109/IConNECT56593.2023.10326776.
[13] J. H. Lubis, M. Mesran, and C. A. Siregar, “The Decision Support System for Cashier Recruitment Implements the Multi-Attribute Utility Theory Method,” Build. Informatics, Technol. Sci., vol. 6, no. 1, pp. 257–264, 2024.
[14] M. N. D. Satria, S. Setiawansyah, and M. Mesran, “Combination of CRITIC Weighting Method and Multi-Attribute Utility Theory in Network Vendor Selection,” Build. Informatics, Technol. Sci., vol. 6, no. 1, pp. 188–197, 2024, doi: 10.47065/bits.v6i1.5342.
[15] S. M. Vadivel, D. S. Shetty, A. H. Sequeira, E. Nagaraj, and V. Sakthivel, “A Sustainable Green Supplier Selection Using CRITIC Method,” in International Conference on Intelligent Systems Design and Applications, Springer, 2023, pp. 308–315. doi: 10.1007/978-3-031-27440-4_29.
[16] S. Hashemkhani Zolfani, F. Ecer, D. Pamučar, and S. Raslanas, “NEIGHBORHOOD SELECTION FOR A NEWCOMER VIA A NOVEL BWM-BASED REVISED MAIRCA INTEGRATED MODEL: A CASE FROM THE COQUIMBO-LA SERENA CONURBATION, CHILE,” Int. J. Strateg. Prop. Manag., vol. 24, no. 2, pp. 102–118, Jan. 2020, doi: 10.3846/ijspm.2020.11543.
[17] M. MARUF and K. ÖZDEMİR, “Ranking of Tourism Web Sites According to Service Performance Criteria with CRITIC and MAIRCA Methods: The Case of Turkey,” Uluslararası Yönetim Akad. Derg., vol. 6, no. 4, pp. 1108–1117, Jan. 2024, doi: 10.33712/mana.1352560.