Evidence-based Employee Performance Evaluation: Integration of Analytical Methods, Digital, and Organizational Perspectives

Authors

  • Nofiyanti Nofiyanti Universitas Insan Pembangunan Indonesia
  • Winanti Winanti Universitas Insan Pembangunan Indonesia
  • Andira Fajrin Sekolah Tinggi Ilmu Komunikasi
  • Sefthian Sefthian Universitas Insan Pembangunan Indonesia
  • Masduki Asbari Universitas Insan Pembangunan Indonesia, Indonesia

DOI:

https://doi.org/10.5555/ijosmas.v6i3.478

Keywords:

Performance Evaluation, Grey Relational Analysis, Balanced Scorecard, Employee Loyalty, Human Resources Scorecard.

Abstract

Employee performance evaluation is a critical component of human resource management, serving as a foundation for strategic organizational decision-making. This study aims to analyze the effectiveness of various performance appraisal methods, including Grey Relational Analysis (GRA), Entropy, Fuzzy Analytical Hierarchy Process (F-AHP), Balanced Scorecard (BSC), and Human Resources Scorecard (HRSC). In addition to quantitative approaches, the study also examines the influence of individual and organizational factors such as self-efficacy, job satisfaction, employee loyalty, and gender mainstreaming on employee performance. The findings reveal that data-driven methods like GRA and F-AHP reduce subjectivity in evaluations, while BSC and HRSC successfully align performance metrics with organizational strategy. Psychosocial factors are also found to significantly contribute to performance improvement. Thus, the implementation of integrated and technology-based evaluation systems is essential for adaptive and strategic human resource performance management

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References

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Published

2025-06-13

How to Cite

Nofiyanti, N., Winanti, W., Fajrin, A., Sefthian, S., & Asbari, M. . (2025). Evidence-based Employee Performance Evaluation: Integration of Analytical Methods, Digital, and Organizational Perspectives. International Journal of Social and Management Studies, 6(3), 8–14. https://doi.org/10.5555/ijosmas.v6i3.478

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