Golden Ratio of Data in Summary
Vol. 6 No. 3 (2026): May - July

Application of Principal Component Analysis in Determining the Factors Influence Turnover Intention of Millennial Generation Employees in Medan City

Ashaya, Marsyela Yulia (Unknown)
Parulian, Edison (Unknown)
Hasyim, Shamir (Unknown)
Julfizar, J. (Unknown)



Article Info

Publish Date
20 May 2026

Abstract

Human resource management is a critical priority that must be continuously enhanced by corporate managers. Effective human resource management is essential for enabling employees to deliver their optimal performance to the company. Conversely, poorly managed employees experience a decline in work motivation and organizational loyalty, which ultimately triggers turnover intention. According to the Deloitte Global Millennial Survey (2019), approximately 49 percent of millennial employees intend to leave their current jobs within the next two years. This study investigates the key factors influencing turnover intention using Principal Component Analysis (PCA) to help companies retain competent human resources and achieve their strategic objectives. The study population comprises millennial employees in Medan City, with a sample of 350 respondents selected via the Lemeshow (1997) technique. Data analysis followed standard PCA procedures, including the Kaiser-Meyer-Olkin (KMO) measure, Bartlett’s Test of Sphericity, correlation matrix examination, factor extraction, and interpretation. The PCA results successfully reduced eight correlating variables into two distinct components: positive internal factors (Job Resources) and work pressure factors (Job Demands).

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Journal Info

Abbrev

grdis

Publisher

Subject

Economics, Econometrics & Finance Social Sciences

Description

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