Covariance Based Structural Equation Modeling dalam Analisis Hubungan Penyesuaian Diri terhadap Culture Shock Mahasiswa Pasca Pandemi Covid-19

Abstract

Structural Equation Modeling (SEM) is a multivariate statistical analysis that can analyze causal relationships between indicator variables and latent variables, and also relationships between latent variables. In this study, covariance-based SEM (CB-SEM) and Maximum Likelihood (ML) estimation were used. This study aims to determine how much correlation and significance between self-adjustment and student culture shock. Based on a survey conducted on S1 Forestry students of the University of North Sumatra showed that 72 respondents were male and 128 respondents were female. For stambuk, it is known that 91 respondents in 2021 and 109 respondents in 2022. The results of the study showed that the value of the Affective latent variable of 40% can be explained by the Introvert and Extrovert Latent variables, and the rest is described by other variables. The resulting value of the latent behavioral variable of 29% can be explained by the affective latent variable and the rest is described by other variables. The resulting value of the Cognitive latent variable of 48% can be explained by the affective, behavioral, extrovert latent and the rest described by the variable. In general, the relationship of self-adaptation with culture shock in the students of the S1 Forest USU is medium-sized. With a high Goodness of Fit (GOF), the model used matches the data.