Analysis of Factors Influencing Entrepreneurial Intention Through a Structural Equation Modeling – Partial Least Squares (Sem-Pls) Approach

Structural Equation Modeling (SEM) is a multivariate statistical analysis method capable of simultaneously examining relationships between variables within a single, complex model. Partial Least Squares (PLS) is one approach to SEM, developed as an alternative to covariance-based SEM (CB-SEM), with the advantage of overcoming sample size limitations and data distribution assumptions. SEM-PLS is prediction-oriented, aiming to maximize explained variance (R²), making it suitable for exploratory research. This study aims to analyze the influence of entrepreneurial education, social support, and campus environment on the entrepreneurial intentions of students in the Faculty of Mathematics and Natural Sciences (FMIPA), University of Lampung. The analysis results show that all indicators have loading factor values above 0.5, thus meeting the convergent validity criteria. The resulting structural model is which indicates that all exogenous variables have a positive effect on entrepreneurial intention. The campus environment variable has the most dominant influence with a coefficient of 0.392, followed by entrepreneurial education at 0.268, and social support at 0.258.