Pengaruh Upah, Motivasi, Kepemimpinan Terhadap Produktivitas Kerja Karyawan Pada Dinas Pertanian Purwodadi

The purpose of this study to analyze the effect of the wage variable to variable labor productivity. Analyze the influence of motivation variable to variable labor productivity. Analyze the influence of leadership variable to variable labor productivity.The population in this study were all employee...

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Main Authors: Fernanda, Melina Lely (Author), , Drs. Ma'ruf, SE. MM (Author)
Format: Book
Published: 2016.
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520 |a The purpose of this study to analyze the effect of the wage variable to variable labor productivity. Analyze the influence of motivation variable to variable labor productivity. Analyze the influence of leadership variable to variable labor productivity.The population in this study were all employees in the Department of Agriculture and the sample is Purwodadi city employees who work in the agricultural service Purwodadi 100 samples. Multiple linear regression equation can be interpreted as follows: The regression coefficient wage variable which means that the variable salary has a positive effect thus increasing productivity. The regression coefficient motivation variable, which means motivation variable has a positive effect thus increasing productivity. The regression coefficient leadership style variable which means that the variables of leadership style has a positive effect thus increasing productivity. The results obtained by t test analysis variable wages have a significant influence on the productivity of labor. Motivation variables have a significant influence on the productivity of labor. Leadership style variable has a significant effect on work productivity at the Department of Agriculture Purwodadi. F test results obtained jointly wage variable, motivation, and the leadership style significantly affects work productivity. Based on the results of Rsquare, meaning labor productivity variable changes the variation can be explained by the variable wage, motivation, and the leadership style. While the rest is explained by other variables outside the model. 
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