<![CDATA[This research is motivated by the author's observations regarding the influence of organizational culture and the provision of incentives on employee performance at the Education and Culture Office of the City of Bukittinggi which shows that organizational culture and provision of incentives are still not in accordance with what is expected and employee performance is still not optimal. The purpose of this study was to obtain data and information about (1) the positive influence of organizational culture on employee performance at the Education and Culture Office of the City of Bukittinggi, (2) the positive effect of providing incentives on employee performance at the Office of Education and Culture of the City of Bukittinggi, This research is a correlational quantitative research with associative type. The population in this study were all employees at the Office of Education and Culture of the City of Bukittinggi totaling 90 employees and the sample was determined using the Cohran formula with an error rate of 10% with the Proportionate Stratified Random Sampling technique obtained 63 employees. The research instrument uses a questionnaire with a Liker scale which has 5 alternative answers. Before the questionnaire was used, trials were carried out to determine its validity and reliability. Data analysis techniques were performed using multiple linear regression tests which were processed using SPSS version 24. The results of data analysis show that there is a significant influence between organizational culture on employee performance with tcount> ttable 2.118> 1.669. There is a significant influence between giving incentives and employee performance with tcount>ttable (2.118>1.669). There is a significant influence between organizational culture and the provision of incentives on employee performance with a value of Fcount>Ftable (1.559> 3.14), so there is a significant influence between organizational culture and provision of incentives jointly on employee performance. The regression table shows a constant value of 59.576 and a regression coefficient of the X1 variable of 0.352 and a regression coefficient of the X2 variable of 0.202. So the multiple linear regression equation used is 59.576+0.352X1+0.202X2+e.]]>
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