<![CDATA[The role of human resources is crucial in the operation of a company. Therefore, companies must enhance employee productivity by providing compensation and rewards for the work they have done. It is expected that if these two points are fulfilled, employee job satisfaction will be achieved. Conversely, if companies neglect these aspects, potential problems may arise within the organization. Our objective is to determine whether compensation and rewards have an impact on job satisfaction among Generation Z employees in Bekasi. This study employs a quantitative method with an explanatory approach. The explanatory approach is chosen to explain how job satisfaction programs can influence organizational sustainability. The data collection technique uses Probability Sampling. The data collection instrument is a questionnaire that serves as the source of primary data, involving 134 respondents in this study. The research data is analyzed using statistical techniques with linear regression to test the effect of variables. This study employs SPSS 29.0 as the statistical testing tool with a total of 20 questionnaire items. The results of this study indicate that the compensation variable (X1) has a direct effect of 0.276 or 27.6% on employee job satisfaction (Y). Meanwhile, the rewards variable (X2) has a direct effect of 0.481 or 48.1% on employee job satisfaction (Y), showing that rewards have a more dominant influence compared to compensation in affecting job satisfaction. The compensation variable (X1) with Sig. = 0.005 on employee job satisfaction (Y) is less than 0.05, which means that the influence of compensation on job satisfaction is statistically significant. Similarly, the rewards variable (X2) with Sig. < 0.001 on employee job satisfaction (Y) is also less than 0.05, indicating that the influence of rewards on job satisfaction is statistically significant. The conclusion from the above explanation is that both compensation (X1) and rewards (X2) have a significant impact on job satisfaction (Y). Rewards have a greater influence (48.1%) compared to compensation (27.6%). There is no multicollinearity issue between the independent variables, making the regression results valid.]]>
