Abstract:
This research aims to know the effect of improving the quality of the leader in organizational and increasingly Job Satisfaction in PT Schott Igar Glass. Based on initial data , there is an indication of the importance for doing this research about the quality of leader in an enterprise involving vertical and horizontal (upward, downward, sideward) communication and also the Job Satisfaction . While the influence of leadership organizational and effectiveness of communication and is a psychological condition that describes the relationship of the employee with his boss and the company ( Meyer& Allen 2005).
As a quantitative research, the researcher use primary data to obtain the data needed for analyzing the influence of leadership organizational & effectiveness communication towards Job Satisfaction. The population in this research is Quality Divison (PT Schott Igar Glass) which is Quality Management, Technical Service and Production. Due to the cost and time limitation, the sample size is chosen to be 120. Questionnaire is used to collect data from respondents. After analzying, found that there is influence of leadership and communication toward (work performance) or Job Satisfaction in PT Schott Igar Glass
Through analysis, the most important thing how make low gap between boss or supervisor towards Quality Divison Employee . So that boss or supervisor can lead better and communicate also motivate them in work. And make some employee enjoy from what they to do (or their job) . And also can be improved their good productivity and increase the quality of good. Results of the analysis found that from the two factors, leadership, and communication have positive and significant impact on Job Satisfaction . HypoSkripsi testing using T-test showed that two independent variables (leadership and communication) significantly affect Job Satisfaction as dependent variables. Then through the F test showed that the variable leadership and communication has a significant effect to Job Satisfaction. Figures adjusted R square of 0.529 indicates that 52.9 percent of Job Satisfaction can be explained by two independent variables used in the regression equation while the rest of 47.1 percent is explained by another variable outside third variables used within this research
