Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Economics, Science, and Education (IJESE)
Drajat Sunaryadi
Sekolah TinggiIlmu Ekonomi Yapan
Economics, Econometrics & Finance Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Human Resource Analytics And Strategic Decision-Making In Human Resource Management: A Systematic Literature Review Drajat Sunaryadi
International Journal of Economics, Science, and Education Vol. 2 No. 5 (2025): International Journal of Economics, Science, and Education (IJESE)
Publisher : CV Pena Jaya Pers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65254/ijese.v2i5.69

Abstract

Purpose:This study aims to systematically review the role of Human Resource Analytics (HRA) in supporting strategic decision-making in Human Resource Management. Design/methodology/approach: A systematic literature review was conducted using peer-reviewed articles indexed in Scopus and SINTA, following PRISMA guidelines with defined inclusion and exclusion criteria. Findings:The results show that Human Resource Analytics enhances strategic HR decision-making in areas such as workforce planning, performance management, talent acquisition, and employee retention. Key dimensions frequently discussed include data quality, analytical capability, technological infrastructure, and managerial support. Research limitations/implications: This review is limited to selected databases and time periods. Future studies should apply longitudinal designs and examine mediating and moderating variables across different organizational contexts. Practical implications:Managers and HR practitioners can use Human Resource Analytics to improve evidence-based strategic HR decisions by strengthening analytical skills and data governance. Originality/value:This study provides an integrated overview of Human Resource Analytics and identifies key themes and directions for future research. Paper type:Literature review
Digital Human Resource Management: A Qualitative Study On Human Resource Transformation In The Era Of Artificial Intelligence Drajat Sunaryadi
International Journal of Economics, Science, and Education Vol. 3 No. 4 (2026): International Journal of Economics, Science, and Education (IJESE)
Publisher : CV Pena Jaya Pers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65254/ijese.v3i4.89

Abstract

Purpose: This study aims to explore the transformation of Human Resource Management (HRM) through the implementation of Digital Human Resource Management (Digital HRM) in the era of Artificial Intelligence (AI). Design/methodology/approach: This study employed a qualitative case study approach. Data were collected through semi-structured interviews, observations, and document analysis involving HR managers and employees. The data were analyzed using the interactive model of Miles, Huberman, and Saldaña, supported by data triangulation to ensure credibility. Findings: The findings indicate that Digital HRM supported by AI has transformed recruitment, employee development, performance management, and talent management. AI enhances operational efficiency, data-driven decision-making, and employee experience. However, successful implementation depends on organizational readiness, digital competencies, ethical AI governance, and effective change management. Research limitations/implications: This study is limited to a single case study. Future research is encouraged to examine multiple organizations and industries using comparative qualitative or mixed-method approaches. Practical implications: The findings provide insights for organizations in developing effective Digital HRM strategies while ensuring ethical AI implementation and sustainable human resource development. Originality/value: This study offers empirical evidence on how Artificial Intelligence supports Human Resource Management transformation and contributes to the growing literature on Digital HRM in the Industry 5.0 era.
Co-Authors