ANALISA GAYA KEPEMIMPINAN DAN KOMUNIKASI DALAM MENINGKATKAN PRESTASI KERJA PADA PT BARELANG MARITIME TRAINING CENTER

Abstract

Any company that has been established to have hope that someday in the future will experience rapid growth in the scope of business of the company. The problems that arise are: a) Is the style of leadership has a significant influence on employees' performance in PT. Barelang Maritime Training Centre?, B) Does the communication method used has a significant influence on employees' performance in PT. Barelang Maritime Training Centre?, C) Is the style of leadership and communication together have a significant effect on employees' performance in PT. Barelang Maritime Training Centre?, D) which of the variables between the leadership and communication that has the most dominant influence in improving employees' performance in PT. Barelang Maritime Training Centre. Data used in this study is the primary data from respondents as many as 65 samples from a total of 168 population. Analysis of the questionnaire answers are distributed to employees of PT. Barelang Maritime Training Centre conducted with SPSS program for Windosws menggunakaan relase 17:00 to test the effect of variable leadership style and communication of employee achievement. The results of this study is that there is influence between the variables of leadership style and employee communications for partial achievement. It is known through the significance of regression coefficients smaller 0.05. Equation is Y = 8328 + +-0.233X2 1.205X1 Variable greatest impact on employee productivity is a style of leadership shown by the regression coefficient of 1.205. While the smallest variable is a variable influence Communications. The magnitude of the coefficient of determination or R2 of 0.909 or 90.9%. Means that 90.9% variation in dependent variable is a variable level of job performance on the multiple regression model can be explained by the independent variable is the variable leadership style and communication while the remaining 9.1% is influenced by variables other than multiple regression models.