Penerapan Kombinasi Metode Pembobotan Entropy dan Technique for Order of Preference by Similarity to Ideal Solution Dalam Pemilihan Karyawan Terbaik
Abstract
The process of selecting the best employees often faces various challenges that can affect the objectivity and fairness of the results. One of the main issues is the objectivity of selecting the best employees, where appraisers may have personal preferences or prejudices that influence their decisions in making the best employee selection. This study aims to apply a more objective and systematic approach in assessing employee criteria and integrate these factors into a more structured decision-making process. By using the entropy weighting method to objectively determine the weight of the criteria and TOPSIS to rank employees based on their proximity to the ideal solution, this study is expected to provide a solid foundation for more accurate and reliable decision-making in human resource management. The application of a combination of entropy weighting and TOPSIS methods in the selection of the best employees offers a comprehensive and structured approach in overcoming the complexity of human resource evaluation. The entropy weighting method is used to objectively determine the weight of the criteria based on data variation, thereby reducing subjectivity in assessment. Meanwhile, TOPSIS is used to rank employees based on their proximity to the positive ideal solution and their distance from the negative ideal solution. The combination of these two methods allows decision-makers to integrate different aspects of employee criteria. The results of the ranking of the best employees gave the results of the first best employee with a final preference score of 0.97858 obtained by Aisyah, the best second employee with a final preference score of 0.79125 obtained by Misri, and the third best employee with a final preference score of 0.69712 obtained by Rudi Setiawan.
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G. Ginting, S. Alvita, M. Mesran, A. Karim, M. Syahrizal, and N. K. Daulay, “Penerapan Complex Proportional Assessment (COPRAS) Dalam Penentuan Kepolisian Sektor Terbaik,” J-SAKTI (Jurnal Sains Komput. dan Inform., vol. 4, no. 2, pp. 616–631, 2020.
H. B. Santoso, I. W. Sriyasa, and P. Citra, “Kombinasi Metode SWARA dan SMART Dalam Sistem Pendukung Keputusan Pemilihan Guru Berprestasi,” J. Artif. Intell. Technol. Inf., vol. 2, no. 1, pp. 38–50, 2024, doi: 10.58602/jaiti.v2i1.102.
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.
A. Aytekin, “DETERMINING CRITERIA WEIGHTS FOR VEHICLE TRACKING SYSTEM SELECTION USING PIPRECIA-S,” J. Process Manag. new Technol., vol. 10, no. 1–2, pp. 115–124, Jun. 2022, doi: 10.5937/jpmnt10-38145.
I. M. Hezam, A. R. Mishra, P. Rani, A. Saha, F. Smarandache, and D. Pamucar, “An integrated decision support framework using single-valued neutrosophic-MASWIP-COPRAS for sustainability assessment of bioenergy production technologies,” Expert Syst. Appl., vol. 211, p. 118674, Jan. 2023, doi: 10.1016/j.eswa.2022.118674.
M. Narang, A. Kumar, and R. Dhawan, “A fuzzy extension of MEREC method using parabolic measure and its applications,” J. Decis. Anal. Intell. Comput., vol. 3, no. 1, pp. 33–46, Apr. 2023, doi: 10.31181/jdaic10020042023n.
Q. Wang, T. Cheng, Y. Lu, H. Liu, R. Zhang, and J. Huang, “Underground Mine Safety and Health: A Hybrid MEREC–CoCoSo System for the Selection of Best Sensor,” Sensors, vol. 24, no. 4, p. 1285, Feb. 2024, doi: 10.3390/s24041285.
H. Dinçer, S. Yüksel, and S. Eti, “Identifying the Right Policies for Increasing the Efficiency of the Renewable Energy Transition with a Novel Fuzzy Decision-Making Model,” J. Soft Comput. Decis. Anal., vol. 1, no. 1, pp. 50–62, Aug. 2023, doi: 10.31181/jscda1120234.
R. Hasanzadeh, P. Mojaver, T. Azdast, S. Khalilarya, A. Chitsaz, and M. A. Rosen, “Decision analysis for plastic waste gasification considering energy, exergy, and environmental criteria using TOPSIS and grey relational analysis,” Process Saf. Environ. Prot., vol. 174, pp. 414–423, Jun. 2023, doi: 10.1016/j.psep.2023.04.028.
M. Mojaver, R. Hasanzadeh, T. Azdast, and C. B. Park, “Comparative study on air gasification of plastic waste and conventional biomass based on coupling of AHP/TOPSIS multi-criteria decision analysis,” Chemosphere, vol. 286, p. 131867, 2022.
A. Yildiz, E. Ayyildiz, A. Taskin Gumus, and C. Ozkan, “A Modified Balanced Scorecard Based Hybrid Pythagorean Fuzzy AHP-Topsis Methodology for ATM Site Selection Problem,” Int. J. Inf. Technol. Decis. Mak., vol. 19, no. 02, pp. 365–384, Mar. 2020, doi: 10.1142/S0219622020500017.
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.
T. Van Dua, D. Van Duc, N. C. Bao, and D. D. Trung, “Integration of objective weighting methods for criteria and MCDM methods: application in material selection,” EUREKA Phys. Eng., no. 2, pp. 131–148, Mar. 2024, doi: 10.21303/2461-4262.2024.003171.
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.
T. Singh, “Entropy weighted WASPAS and MACBETH approaches for optimizing the performance of solar water heating system,” Case Stud. Therm. Eng., vol. 53, p. 103922, Jan. 2024, doi: 10.1016/j.csite.2023.103922.
L. Zhang, Q. Cheng, and S. Qu, “Evaluation of Railway Transportation Performance Based on CRITIC-Relative Entropy Method in China,” J. Adv. Transp., vol. 2023, pp. 1–11, Mar. 2023, doi: 10.1155/2023/5257482.
H. Yuan, X. Ma, Z. Cheng, and T. Kari, “Dynamic Comprehensive Evaluation of a 660 MW Ultra-Supercritical Coal-Fired Unit Based on Improved Criteria Importance through Inter-Criteria Correlation and Entropy Weight Method,” Energies, vol. 17, no. 7, p. 1765, Apr. 2024, doi: 10.3390/en17071765.
R. Supardi and A. Sudarsono, “Penerapan Metode Weighted Product (WP) Dalam Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Pada PT. Agrodehasen Bengkulu,” J. MEDIA INFOTAMA, vol. 19, no. 1, pp. 141–147, 2023.
I. Ramadhan and D. C. P. Buani, “Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Berdasarkan Kinerja Dengan Metode Analytical Hierarchy Process (AHP),” EVOLUSI J. Sains dan Manaj., vol. 11, no. 1, 2023.
V. H. Saputra and S. Setiawansyah, “Penerapan Metode SWARA dan Grey Relational Analysis Dalam Pemilihan Karyawan Terbaik,” J. Artif. Intell. Technol. Inf., vol. 2, no. 1, pp. 51–61, 2024, doi: 10.58602/jaiti.v2i1.107.
B. Maitasari and A. Farisi, “Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Maut,” SATESI J. Sains Teknol. dan Sist. Inf., vol. 4, no. 1, pp. 17–23, 2024.
R. Hernanda, “Pemilihan Karyawan Terbaik Di Erafone Menggunakan Metode SAW,” J. Sist. Inf. dan Apl., vol. 2, no. 1, pp. 60–67, 2024.
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.
E. Pranita, J. P. Sembiring, A. Jayadi, N. U. Putri, A. Jaenul, and A. M. Fathurahman, “Melinjo Chip Dryer Monitoring System Using Fuzzy Logic Method,” in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), Aug. 2023, pp. 98–102. doi: 10.1109/IConNECT56593.2023.10327339.
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