Kombinasi Metode Pembobotan Entropy dan MARCOS Dalam Seleksi Penerimaan Karyawan Divisi Keuangan

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.

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Publication Details

Journal
Building of Informatics Technology and Science (BITS)
Published
2024-12-25
DOI
https://doi.org/10.47065/bits.v6i3.5835
Primary Topic
Management and Optimization Techniques
Type
article
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article

Kombinasi Metode Pembobotan Entropy dan MARCOS Dalam Seleksi Penerimaan Karyawan Divisi Keuangan

Dita Septia Wahyuni, Adhie Thyo Priandika
Building of Informatics Technology and Science (BITS)
Management and Optimization Techniques
article

Kombinasi Metode Pembobotan Entropy dan MARCOS Dalam Seleksi Penerimaan Karyawan Divisi Keuangan

Dita Septia Wahyuni, Adhie Thyo Priandika
article en

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.

Building of Informatics Technology and Science (BITS)Vol. 6(3)
Universitas Teknokrat Indonesia (ID)
Openalex Percentile: Top 50%
Management and Optimization Techniques
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