Applying machine learning in data analytics of human resource management

Các tác giả

  • Nguyễn Phát Đạt
    University of Economics and Law, Ho Chi Minh City Vietnam National University Ho Chi Minh City, Việt Nam
  • Nguyễn Văn Hồ
    University of Economics and Law, Ho Chi Minh City Vietnam National University Ho Chi Minh City, Việt Nam
  • Thái Kim Phụng
    College of Technology and Design, University of Economics Ho Chi Minh City, Việt Nam

DOI:

10.46223/HCMCOUJS.econ.vi.19.9.3193.2024

Từ khóa:

HRM; machine learning; employee attrition; human resource management

Phân loại JEL:

C61; C63; C67

Tóm tắt

Human Resource Management (HRM) plays a crucial role in achieving organizational success by effectively managing the workforce. Every business success has numerous contributions from employees at all levels. However, this becomes an intense dilemma when they leave, which leads to business delays and lower performance. Therefore, employee retention management plays a vital role, which, if well-controlled can enhance the business performance. This research suggests an employee attrition prediction model as well as reports to have an overall view of IBM’s HR dataset. The authors proposed machine learning models to predict employees who left the company: Logistics Regression, K-nearest Neighbors, Decision Tree, Support Vector Machine, Neural Network, and Random Forest. In addition, dashboard reports are also created to support an executive view for business decision-making. By implementing the proposed models and building dashboards, organizations can make use of valuable output to drive suitable strategic HRM decisions and gain meaningful results for business.

Tải xuống

Dữ liệu tải xuống chưa có sẵn.

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Tải xuống

Ngày nộp: 16-01-2024
Ngày duyệt đăng: 21-03-2024
Ngày xuất bản: 20-07-2024

Thống kê truy cập

Trang tóm tắt: 951
PDF: 907

Cách trích dẫn

Đạt, N. P., Hồ, N. V., & Phụng, T. K. (2024). Applying machine learning in data analytics of human resource management. TẠP CHÍ KHOA HỌC ĐẠI HỌC MỞ THÀNH PHỐ HỒ CHÍ MINH - KINH TẾ VÀ QUẢN TRỊ KINH DOANH, 19(9), 96–108. https://doi.org/10.46223/HCMCOUJS.econ.vi.19.9.3193.2024