This study used JASP software to process the primary data and conduct analyses using structural equation modeling (SEM), partial least squares (PLS), and bootstrap significance testing. The results showed a strong positive total effect between job satisfaction as the dependent variable and work culture as the independent variable JASP, an acronym for Jeffrey’s amazing statistical program, honors the Bayesian statistician Sir Harold Jeffreys. The study examined key statistical components, including model fit, BIC, AIC, fit indices, additional fit measures, R² values, factor loadings, factor variance, regression coefficients, weights, and residual variance. Data collection followed a quantitative survey approach at metro mass transit, focusing on 138 full-time drivers, with a final sample of 102 determined through Krejcie and Morgan’s (1970) formula. A deductive approach was implemented using probability sampling. The hypothesis was confirmed. This research seeks to enhance the educational utility of JASP by providing comparative statistical analyses for improved clarity and differentiation.
