@article{Marliana_Suhayati_Handayani N._2022, title={Bayesian-Structural Equation Modeling on Learning Motivation of Undergraduate Students During Covid-19 Outbreak}, volume={6}, url={https://journal.stats.id/index.php/ijsa/article/view/832}, DOI={10.29244/ijsa.v6i1p63-76}, abstractNote={<p>The aim of this study is to explore the relationship model between e-learning readiness, self-directed learning readiness, and learning motivation of the students at STMIK Sumedang during the COVID-19 outbreak. Bayesian-Structural Equation Modeling and Markov Chain Monte Carlo Algorithm are used in the estimation of the parameters. The posterior distribution is formed using informative prior i.e., inverse-Gamma distribution on variance parameters, inverse-Wishart distribution on residual covariance, and normal distribution on other parameters of the model. The calculation is performed using the blavaan package on R-Software version 4.1.0 with 19000 iteration and 9000 samples of burn-in period. Data were taken from 214 samples of the students at STMIK Sumedang. The outcome from the calculation showed there is a significant effect from self-directed learning readiness to motivation learning of students and there is no significant effect from e-learning readiness to learning motivation. The direct effect on learning motivation is 7.25 from self-directed learning readiness and 0.045 from e-learning readiness.</p>}, number={1}, journal={Indonesian Journal of Statistics and Its Applications}, author={Marliana, Reny Rian and Suhayati, Maya and Handayani N., Sri Bekti}, year={2022}, month={May}, pages={63–76} }