Application of Principal Component Analysis (PCA) in Determining the Dominant Factors Affecting Women’s Interest in Entrepreneurship in the Lower Market of Bukittinggi - -, Nafisatuzzahara SY; Prima Sari, Devni (Journal of Statistics and Data Science, 2025)
The success of women in traditional markets is often constrained by various interrelated factors that directly affect the local economy. This study aims to identify the dominant factors influencing women's interest in entrepreneurship at Pasar Bawah, Bukittinggi, using the Principal Component Analysis (PCA) method. Primary data were collected through questionnaires distributed to women entrepreneurs, covering variables such as job choice, entrepreneurial interest, self-empowerment, social environment, and risk tolerance. PCA was applied to reduce correlated variables into fewer uncorrelated principal components. The analysis resulted in three principal components, with the first component selected as the dominant factor due to its highest explained variance. This component, with an eigenvalue of 4.73, explains 47.35% of the total variance and includes variables such as interest in entrepreneurship, willingness to take risks, feeling empowered and useful, and high self-confidence. These findings highlight the importance of psychological and personal factors in women's entrepreneurial interest.   The study suggests that government policies should focus on inclusive support such as access to microcredit, digital entrepreneurship training, and promotion of local products to improve the competitiveness of traditional markets and empower women entrepreneurs.