Perbandingan LLM pada OpenAI untuk Mengevaluasi Kinerja Pegawai di PT Javan Cipta Solusi

Novi Setiani

Abstract

. Evaluating the performance of the best employees in a company is a common problem faced by the human resources division. Assessing subjectively and comprehensively is a challenge that must be overcome in building sustainable business growth. For organizations that are already able to manage employee assignment data in a structured and systematic form, this can be done by processing quantitative data obtained from the task management system. In this study, a large language model-based approach is proposed to identify the best employees based on assignment data for one year. A comparison was made of six versions of LLM on OpenAI to measure employee performance based on a predetermined prompting design. As a result, 50% of respondents considered that the criteria proposed by GPT4o-mini were more appropriate to their needs, and 60% of respondents considered that the employee ranking results produced by GPT-4 were more relevant to the reality.

Full Text:

PDF

References

Aksakal, E., & Dağdeviren, M. (2014). Analyzing reward management framework with multi criteria decision making methods. Procedia-Social and Behavioral Sciences, 147, 147-152.

Apriadi, D., Susena, K. C., & Irwanto, T. (2020). Analisis Kinerja Pegawai Pada Kantor Kesbangpol Kabupaten Kaur Performance Analysis Of Employees In Kesbangpol Office Kaur District. Journal Bima (Business, Management And Accounting), 1(2), 97-105.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901.

Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019, June). Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers) (pp. 4171-4186).

Ijadi Maghsoodi, A., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy. Frontiers of Business Research in China, 12(1), 2.

Kharub, M., Mondal, S., Singh, S., & Gupta, H. (2025). Evaluation of competency dimensions for employee performance assessment: evidence from micro, small, and medium enterprises. International Journal of Productivity and Performance Management, 74(1), 107-138.

Na-Nan, K., Chaiprasit, K., & Pukkeeree, P. (2018). Factor analysis-validated comprehensive employee job performance scale. International Journal of Quality & Reliability Management, 35(10), 2436-2449.

Shi, J. L., & Lai, W. H. (2023). Fuzzy AHP approach to evaluate incentive factors of high-tech talent agglomeration. Expert systems with applications, 212, 118652.

DOI: https://doi.org/10.31284/j.integer.2026.v11i1.8169

Refbacks

  • There are currently no refbacks.