APPLICATION OF STRUCTURAL EQUATION MODELING (SEM) IN ANALYZING ACADEMIC PERFORMANCE

Abstract

Academic performance is one of the ways to determine whether one has had a good education. There are multiple factors that can influence someone’s academic performance. The multivariate model in Structural Equation Modeling (SEM) is used to determine the relations between level of stress, level of resilience, and academic performance. The data for this study is collected using google form, distributed to active students of Prasetiya Mulya. The SEM model in this study is a combination of multivariate regression analysis and confirmatory factor analysis called structural regression model. There are three hypotheses made in this study. The modelled hypotheses will then be evaluated using a chi-square test, Root Means Squared Error of Approximation (RMSEA), Tucker Lewis Index (TLI), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The chi square test shows that two of the three models are significant with the first model being the best one out of the three. The first model, which states that resilience and stress affect students’ academic performance, but stress and resilience have no correlation with one another, shows minimal discrepancy between the data and model estimation, shown by the chi square p-value of 0.454, RMSEA of 0.005, and TLI of 1.