<![CDATA[This research aims to analyze the effect of performance incentives and leadership towards functional official in inspectorat office of East Kutai district area. This research is done by field research field (Field Work Research) through observation, interviews and questionnare. Research population number were 44 people, thus the sample taken from all of the population. The sampling technique used was census method because based on the look of the region, this research only covers a very narrow area. The basic theory used in this study is Human Resource Management that focuses on the discussion of regional incentives area, performance and leadership. This research using two analysis tools that is classical analysis assumptions which are Heteroskidastity with Glejser Test, Multicolinearity Test with seeing Tolerance Value and VIF, and Auto Correlation Testing Test with Durbin Watson Test, and Multiple Linear Regression Analysis with Hypothesis Test that is Partial Test / T Test, Simultaneous Test / F test and Coefficient of Determination Testing (R2). Based on the results of the calculation are known multiple regression equation as follows : Y = 2.416 + 0.043 + 0.310 X1 X2. Leadership Hypothesis Testing (X1) partially on Performance Officer (Y). Leadership variables (X1) don’t have significant positive effect on the Official Performance variables (Y). Incentive variables (X2) have significant positive effect on the Official Performance variables (Y). The proposed hypothesis is accepted. Leadership (X1) and Incentives (X2) hypothesis testing simultaneously / together are positive and have significant effect on Officials Performance (Y). So, it can concluded that the leadership variable (X1), and incentives variable (X2) simultaneously / together have a significant impact on official performance (Y), with the significancy value results are sig = 0.000 <0.05. Coefficient of Determination testing, showed that oficial performance can be affected by officials Leadership (X1), and Incentives (X2) variables by the value of 0.324 or 32.4 while the remaining 67.6% is influenced by other variables beyond those independent variables that were not included in the research model]]>
