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Nisya, Nur Aeinun
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Designing Recruitment Automation System to Reduce Gender, Age, Race, and Educational Background Bias in Indonesia Nisya, Nur Aeinun; Riani, Lilia Pasca
Proceeding Kilisuci International Conference on Economic & Business Vol. 3 (2025): Proceeding Kilisuci International Conference on Economic and Business
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/kilisuci.v3i.7143

Abstract

Research aim: This research aims to design a fair, technology-based recruitment system by eliminating bias and assessing candidates solely based on their competence. Design/Method/Approach: This research utilizes the ADDIE model to develop a bias-free recruitment system. Research Finding: The system effectively identifies and minimizes bias in candidate selection by prioritizing relevant qualifications and competencies, while excluding non-work-related factors. Theoretical contribution/Originality: This research enhances the understanding of automation in employee recruitment in developing countries, particularly Indonesia, by introducing innovative recruitment algorithms that promote diversity and inclusivity across various companies. Practical/Policy Implication: This research suggests that companies adopt a more equitable automation system to foster a diverse and innovative work environment. Research limitation: This study requires further validation with large-scale, real-world data. Future research should utilize more diverse datasets and explore the system’s impact in a broader context.
Co-Authors Lilia Pasca Riani