AI Based Employee Attrition Prediction Tool

Author:

Agarwal Swati,Bhardwaj Chetna,Gatkamani Glory,Gururaj Raghav,Darapaneni Narayana,Paduri Anwesh Reddy

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Kapoor, E.: Great resignation impact being felt in India as attrition rate remains elevated at 20% in 2022. In: Business Insider India (2022). https://www.businessinsider.in/careers/news/great-resignation-impact-being-felt-in-india-as-attrition-rate-remains-elevated-at-20-in-2022/articleshow/94453768.cms. Accessed 02 May 2023

2. Shinde, S.: IT industry logged 25% attrition in FY22, trend to continue: Report. Business Standard (2022). https://www.business-standard.com/article/economy-policy/it-industry-logged-25-attrition-in-fy22-trend-to-continue-report-122092900620_1.html. Accessed 02 May 2023

3. Raza, A., Munir, K., Almutairi, M., Younas, F., Fareed, M.M.S.: Predicting employee attrition using machine learning approaches. Appl. Sci. (Basel) 12(13), 6424 (2022)

4. “7 statistics on employee turnover every HR manager should be aware of,” Workforce.com. https://workforce.com/news/7-statistics-on-employee-turnover-in-2022-every-hr-manager-should-be-aware-of. Accessed 02 May 2023

5. “Employee retention,” Akkio. https://www.akkio.com/applications/employee-retention. Accessed 02 May 2023

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