<![CDATA[In the study, the population was the Air Crew of the Air Police Directorate totaling 200, a sample of 20% of the population of 40 people. The t-value for X1 (Work-Life Balance) was 2.691, the t-table value for N = 40 was 2.021. So 2.691> 2.021, because t count> t table, then H0 is rejected and Ha is accepted, it is concluded that Work-Life Balance (X1) has an influence on Work Commitment, The t-value for variable X2 (Job Stress) was 2.573, while the t-table value for N = 40 was 2.021. So 2.573> 2.021, because t count> t table, then H0 is rejected and Ha is accepted, it can be concluded that Work Stress (X2) has a good influence in improving service quality, This is evident from the results obtained that the t-value is greater than the t-table value. In the ANOVA results above, it shows the F count value for both variables, namely Work-Life Balance (X1) and Job Stress (X2), the F count value is 7.860. While F table ( 0.05) N = 40 is 2.84. So F count > F table or 7.860 > 2.84. Thus H0 is rejected and Ha is accepted. It can be concluded that between Work Life Balance and Job Stress together (simultaneously) have a good effect in increasing Work Commitment. This is proven by the calculated F value obtained is greater than the F table value that has been set. The R value (large) shows the combined relationship between the two independent variables X1 and X2 to the dependent variable Y is 0.546. This shows that the two independent variables, namely X1 and X2, together have a significant relationship of 54.6%. The remaining 45.4% is related to other factors. And the R Square value of 0.298 means that the two variables X1 and X2 together have an effect of 29.8% and the remaining 70.2% is influenced by other factors not observed by the author.]]>
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