Kombinasi Metode Pembobotan Entropy dan MARCOS Dalam Seleksi Penerimaan Karyawan Divisi Keuangan
Abstract
The selection of employees for the Finance Division is a crucial process to ensure that the selected individuals have the appropriate skills and qualifications to handle complex financial responsibilities. The main problems in the selection of Finance Division employees often revolve around the difficulty in accurately assessing the candidate's technical skills and analytical abilities. The experience and qualifications listed on a resume do not necessarily reflect the candidate's apparent ability to handle complex financial situations or in the face of stringent regulatory challenges. This study aims to apply a combination of entropy and MARCOS weighting methods in the selection of employees of the Finance Division, in order to improve the objectivity and accuracy of the decision-making process. Through this approach, to identify candidates who best suit the company's needs and requirements based on a comprehensive multi-criteria analysis. The combination of Entropy and MARCOS weighting methods in the selection of financial division employees provides a comprehensive and objective approach in decision-making. The Entropy method is used to objectively determine the weight of the criteria based on the degree of uncertainty of the information provided by each criterion, the MARCOS method is used to evaluate and rank candidates based on their proximity to the ideal solution and the distance from the anti-ideal solution. The results of the financial division employee acceptance selection ranking show that Budi Santoso occupies the top position with the highest score of 4.8848. These results provide a clear picture of each candidate's relative position in terms of final assessment, and can serve as a basis for more targeted and objective hiring decisions.
Downloads
References
A. Soussi, A. M. Tomasoni, E. Zero, and R. Sacile, “An ICT-Based Decision Support System (DSS) for the Safety Transport of Dangerous Goods along the Liguria and Tuscany Mediterranean Coast,” in Intelligent Sustainable Systems: Selected Papers of WorldS4 2022, Volume 2, Springer, 2023, pp. 629–638. doi: 10.1007/978-981-19-7663-6_59.
J.-S. Lin and K.-H. Chen, “A novel decision support system based on computational intelligence and machine learning: Towards zero-defect manufacturing in injection molding,” J. Ind. Inf. Integr., vol. 40, p. 100621, Jul. 2024, doi: 10.1016/j.jii.2024.100621.
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.
H. Yousefi, S. Moradi, R. Zahedi, and Z. Ranjbar, “Developed analytic hierarchy process and multi criteria decision support system for wind farm site selection using GIS: A regional-scale application with environmental responsibility,” Energy Convers. Manag. X, vol. 22, p. 100594, 2024, doi: 10.1016/j.ecmx.2024.100594.
M. Qiyas, T. Madrar, S. Khan, S. Abdullah, T. Botmart, and A. Jirawattanapaint, “Decision support system based on fuzzy credibility Dombi aggregation operators and modified TOPSIS method,” AIMS Math., vol. 7, no. 10, pp. 19057–19082, 2022, doi: 10.3934/math.20221047.
D. D. Trung and H. X. Thinh, “A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study,” Adv. Prod. Eng. Manag., vol. 16, no. 4, pp. 443–456, Dec. 2021, doi: 10.14743/apem2021.4.412.
M. Bitarafan, K. A. Hosseini, and S. H. Zolfani, “Identification and assessment of man-made threats to cities using integrated Grey BWM- Grey MARCOS method,” Decis. Mak. Appl. Manag. Eng., vol. 6, no. 2, pp. 581–599, Oct. 2023, doi: 10.31181/dmame622023747.
S. Bošković, L. Švadlenka, M. Dobrodolac, S. Jovčić, and M. Zanne, “An Extended AROMAN Method for Cargo Bike Delivery Concept Selection,” Decis. Mak. Adv., vol. 1, no. 1, pp. 1–9, Jun. 2023, doi: 10.31181/v120231.
S. H. Hadad, A. R Metha, S. Setiawansyah, and H. Sulistiani, “Evaluation of Salesperson Performance in the Sales Allowance Decision Support System Using the MARCOS and PIPRECIA Methods,” J. Comput. Syst. Informatics, vol. 5, no. 2, pp. 477–486, Feb. 2024, doi: 10.47065/josyc.v5i2.4863.
F. Ecer, A. Böyükaslan, and S. Hashemkhani Zolfani, “Evaluation of Cryptocurrencies for Investment Decisions in the Era of Industry 4.0: A Borda Count-Based Intuitionistic Fuzzy Set Extensions EDAS-MAIRCA-MARCOS Multi-Criteria Methodology,” Axioms, vol. 11, no. 8, p. 404, Aug. 2022, doi: 10.3390/axioms11080404.
P. Citra, H. B. Santoso, and I. W. Sriyasa, “Sistem Pendukung Keputusan Pemilihan E-Commerce Menggunakan Pembobotan Entropy dan COPRAS,” J. Ilm. Inform. dan Ilmu Komput., vol. 3, no. 1, pp. 36–45, 2024, doi: 10.58602/jima-ilkom.v3i1.25.
A. Puška, A. Štilić, and I. Stojanović, “Approach for multi-criteria ranking of Balkan countries based on the index of economic freedom,” J. Decis. Anal. Intell. Comput., vol. 3, no. 1, pp. 1–14, Dec. 2023, doi: 10.31181/jdaic10017022023p.
I. Mukhametzyanov, “Specific character of objective methods for determining weights of criteria in MCDM problems: Entropy, CRITIC and SD,” Decis. Mak. Appl. Manag. Eng., vol. 4, no. 2, pp. 76–105, Oct. 2021, doi: 10.31181/dmame210402076i.
M. W. Arshad, S. Setiawansyah, and M. Mesran, “Implementation of Entropy and Additive Ratio Assessment Methods in Determining the Best Warehouse Location,” Bull. Comput. Sci. Res., vol. 4, no. 4, pp. 318–326, 2024, doi: 10.47065/bulletincsr.v4i4.360.
A. Apriani, I. G. D. Santana Dharma, M. Mayadi, and N. G. A. Dasriani, “Sistem Pendukung Keputusan Seleksi Penerimaan Karyawan dengan Metode AHP dan Pembobotan Fuzzy,” J. Bumigora Inf. Technol., vol. 4, no. 1, pp. 59–72, Jun. 2022, doi: 10.30812/bite.v4i1.1915.
I. Iqbal and R. Juliansyah, “Sistem Pendukung Keputusan Seleksi Penerimaan Karyawan Rumah Sakit Bmc Dengan Menggunakan Metode Promethee,” J. TIKA, vol. 8, no. 1, Apr. 2023, doi: 10.51179/tika.v8i1.1936.
R. Hamdani, S. F. Rezky, and D. Suherdi, “Penerapan Fuzzy Logic Dalam Seleksi Penerimaan Karyawan Internship Content Writer Pada PT Boxity Central Indonesia: Penerapan Fuzzy Logic Dalam Seleksi Penerimaan Karyawan Internship Content Writer Pada PT Boxity Central Indonesia,” J. SAINTIKOM (Jurnal Sains Manaj. Inform. dan Komputer), vol. 23, no. 2, pp. 331–340, 2024, doi: 10.53513/jis.v23i2.10238.
S. Luneto, “Sistem Pendukung Keputusan Seleksi Penerimaan Karyawan Baru di Soto Seger Hj. Fatimah dengan Metode Multi-Objective Optimization by Ratio Analysis (MOORA),” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 11, no. 1, 2024, doi: 10.35957/jatisi.v11i1.7633.
A. Pramuditya, D. Darwis, and S. Setiawansyah, “Kombinasi Logarithmic Percentage Change-Driven Objective Weighting dan Complex Proportional Assessment Dalam Penentuan Supplier Perlengkapan Olahraga,” J. Comput. Syst. Informatics, vol. 5, no. 3, pp. 660–669, 2024, doi: 10.47065/josyc.v5i3.5160.
R. R. Purba, M. Mesran, M. T. A. Zaen, S. Setiawansyah, D. Siregar, and E. W. Ambarsari, “Decision Support System in the Best Selection Coffee Shop with TOPSIS Method,” IJICS (International J. Informatics Comput. Sci., vol. 7, no. 1, p. 28, Mar. 2023, doi: 10.30865/ijics.v7i1.6157.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Kombinasi Metode Pembobotan Entropy dan MARCOS Dalam Seleksi Penerimaan Karyawan Divisi Keuangan
Pages: 1848-1859
Copyright (c) 2024 Dita Septia Wahyuni, Adhie Thyo Priandika

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).