<![CDATA[Implementation of PLS-SEM in educational research has developed significantly, but there are variations in the presentation of the analysis results. This study aims to provide practical understanding to researchers who intend to utilize PLS-SEM in multivariate analysis to enhance the recognition and validity of the resultant research outcomes using SmartPLS. This research is a literature study that conducts content analysis of relevant books and publications. The research results present PLS-SEM analysis using SmartPLS on reflective and formative research models with first-order and second-order approaches through measurement model evaluation (outer model) and structural model evaluation (inner model) with various criteria. Evaluation of the reflective measurement model consists of reflective indicator loadings, internal consistency reliability, convergent validity, and discriminant validity. The review of the formative measurement model consists of convergent validity, collinearity, and statistical significance of weights. The structural model evaluation consists of the collinearity test, significance value, f square, R square, Q square, SRMR, PLSpredict, and robustness checks. Therefore, this study can provide guidance using SmartPLS in conducting PLS-SEM analysis and presenting acceptable analysis results.]]>
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