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The company has a goal to meet market demand, increase competitiveness and improve performance. Achievement of these goals shows the results of the work owned by resources, especially from HR so that many companies implement HR management systems as a way to maximize the ability of employees to improve performance towards organizational optimization. One step in HR management is to make sure they are satisfied with their work. Job satisfaction as a positive or negative attitude towards work so that if an employee feels satisfied, he will contribute optimally. Job satisfaction is also assessed from the suitability of the work with the personality of the person who is doing it, so that in carrying out work rotation, the company needs to pay attention to this further. This research was conducted in the Wilayah Telkom Lampung with the achievement in 2018 of 90.27%. The percentage of employees experiencing job rotation during 2018 is 23% of total employees and the level of job satisfaction is 90% on work rotation. This is a concern even though employees are satisfied with work rotation, but 94% employee performance is only categorized as P3. The purpose of this study was to determine the effect of job rotation on performance, determine the effect of job rotation on job satisfaction, determine the effect of job satisfaction on performance and determine the role of job satisfaction as a mediator between job rotation on performance. The design of this study is causal research by seeking explanations in the form of a causal relationship between several variables. The analysis approach uses a quantitative data collection approach that examines the population with the method of collecting data using a questionnaire. Questionnaire measurement uses a Likert scale with 68 respondents. Analysis of data processing in this study uses multiple linear regression analysis to see the distribution of data, and in this study there are mediating variables that theoretically can affect the causal relationship between independent variables and dependent variables so that they are further processed using regression analysis of the Causal Step method and Product Coefficients.