<![CDATA[The results of multiple linear regression show that the calculated T value for the Human Resource Quality variable is greater than the T table value. This means that the variable has a significant influence on the dependent variable in the regression model. In addition, the level of significance (p-value) below the standard of 0.05 indicates that the results are statistically significant. This means that the human resource quality variable has a meaningful relationship with the dependent variable, and this relationship is most likely not due to chance. Overall, if both criteria (the calculated T value is greater than the T table and the level of significance is below 0.05) are met, then it can be concluded that the quality of human resources has a significant effect on the variables you are studying. If the quality of human resources improves, then client satisfaction tends to increase. This is because good human resource quality often reflects better ability to provide services, effective communication, and understanding of client needs. All of these factors contribute positively to the client experience, which ultimately increases their satisfaction. In the context of the previously mentioned regression, if the human resource quality variable has a significant effect on client satisfaction, then this increase in quality will most likely lead to an increase in client satisfaction. Based on the results of the second hypothesis with the calculated T value of the public service quality variable greater than the T table and the significance value below the standard of 0.5, this indicates that the null hypothesis (H0) is rejected. In other words, there is a significant influence of the public service quality variable on the variables tested in your study. The significance value below the standard of 0.5 (usually used 0.05 in research) indicates that the results are very statistically significant. If the quality of public service improves, then client satisfaction tends to increase. Better service quality usually includes speed, effectiveness, friendliness, and meeting client needs appropriately, all of which contribute positively to the level of client satisfaction. Quality service provides a more satisfying experience for clients, so they feel appreciated and treated well, which ultimately increases their satisfaction. In addition, the value of 2 = 0.610 R 2 = 0.610 or 61% shows that 61% of the variation in customer satisfaction can be explained by the quality of human resources and service quality. The remaining 39% represents the variation not explained by the variables in the model, indicating that other factors can also affect customer satisfaction. These results indicate the importance of focusing on improving both human resource quality and customer service quality to improve customer satisfaction. If there is interest, we can explore what other variables can be included to explain the remaining variation]]>
