Research using multiple linear analysis, correlation coefficient analysis, calculating the coefficient of determination, as well as testing the hypothesis by looking for the value of t count, then comparing t count with t table, and testing the hypothesis by looking for the calculated f value, then compares f count with f table. The results of the analysis obtained with the following details:From the results of multiple linear analysis, the equation Y = 1.392 + 0.349 X1 + 0.616 X2, and from the results of the correlation coefficient, job mutations have a positive and very strong correlation to the level of employee performance, which is 0.790, job mutations and recruitment have a positive and very positive correlation. strong on the level of employee performance that is equal to 0.850.Based on the results of the hypothesis test, the t-count for recruitment is 4.078, the t-count for work motivation is 9.241, with a t-table of 1.67722 obtained from the t-table distribution for df = 50 – 2 and the level of significance is 0.05. In other words, Ha is accepted and Ho is rejected, because t count > t table. Based on the hypothesis test for model 1, the f arithmetic result is 79.587, for model 2 the f arithmetic result is 61.067, with f table 1.45 with a significant level of 0.000, the number 0.000 < 0.05, thus Ho is rejected and Ha is accepted, because f count > f table