Proceedings of the International Conference on Applied Science and Technology on Social Science 2023 (iCAST-SS 2023)

Enhancing Employee Quality through Objective Evaluation: A Delphi-AHP Approach for Selecting Best Employees at McEasy Company

Authors
Rosiyah Faradisa1, *, Salsabila Ananda Madani1, Mu’arifin M1, Moh Hasbi Assidiqi2, Tessy Badriyah3
1Department of Informatics and Computer Engineering, Surabaya, Indonesia
2Department of Creative Multimedia Technologies, Surabaya, Indonesia
3Electronic Engineering Polytechnic Institute of Surabaya, Surabaya, Indonesia
*Corresponding author. Email: faradisa@pens.ac.id
Corresponding Author
Rosiyah Faradisa
Available Online 15 February 2024.
DOI
10.2991/978-2-38476-202-6_12How to use a DOI?
Keywords
—employee performance evaluation; decision support system; selection criteria; Delphi; AHP
Abstract

Employees are one of the company’s main assets whose quality must be continuously improved. Evaluation of employee performance in the form of selecting the best employees is one of the efforts that can be made to improve the quality of the company’s human resources. McEasy Company has conducted a selection of the best employees every year. Selection is made through voting by related parties without clear and measurable assessment parameters so it tends to be subjective towards the views of each assessor. In this study, factors or criteria for evaluating employees will be sought which are measurable and agreed upon by the relevant parties (panelists). The Delphi-AHP method will be applied to obtain these criteria. Through the Delphi 2-round method, a consensus on employee assessment points was obtained from the panelists, and through the calculation of the AHP method, the weight was obtained as the value of relative importance or the contribution scale of each factor. From the results obtained, the 3 factors with the highest ratings were work finish on time (31.21%), good communication skills (16%), and good time management (11.5%). The results obtained can then be used in evaluating the best employees at the McEasy company. Furthermore, the results of this study can be embedded in an information system as a feature of the decision support system for selecting the best employees. Where factor weights can be adjusted through the system, and the appraiser can assess directly without the need to know the weight of each of these factors.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applied Science and Technology on Social Science 2023 (iCAST-SS 2023)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
15 February 2024
ISBN
978-2-38476-202-6
ISSN
2352-5398
DOI
10.2991/978-2-38476-202-6_12How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Rosiyah Faradisa
AU  - Salsabila Ananda Madani
AU  - Mu’arifin M
AU  - Moh Hasbi Assidiqi
AU  - Tessy Badriyah
PY  - 2024
DA  - 2024/02/15
TI  - Enhancing Employee Quality through Objective Evaluation: A Delphi-AHP Approach for Selecting Best Employees at McEasy Company
BT  - Proceedings of the International Conference on Applied Science and Technology on Social Science 2023 (iCAST-SS 2023)
PB  - Atlantis Press
SP  - 80
EP  - 88
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-202-6_12
DO  - 10.2991/978-2-38476-202-6_12
ID  - Faradisa2024
ER  -