Pengaruh Beban Kerja dan Motivasi terhadap Kinerja Karyawan pada PT.MAPR
DOI:
https://doi.org/10.61132/lokawati.v3i5.2070Keywords:
Workload, Motivation, Employee PerformanceAbstract
The problem in the research is that the work given exceeds the provisions of written regulations, company leaders do not pay enough attention to their employees or do not provide enough motivation to their employees, performance fluctuates from year to year because employees are less careful in their work. The aim of this research is to determine the workload and motivation of employee performance at PT. Mandiri Abadi Permai. The type of this research is quantitative. The population in this research is employees of PT. Mandiri Abadi Permai, totaling 140 respondents. Determining the number of samples using the Slovin formula was 58 respondents, while the sampling technique was carried out randomly. The data sources in this research are primary and secondary data. Then the data collection methods in this research are observation, interviews, questionnaires and documentation. Meanwhile, the data analysis technique used is multiple linear regression analysis. Multiple linear regression test results Y=8.137+0.5221+0.532X2+e. The results of the test (t) or partial test show that workload has a positive and significant effect on employee performance which can be seen from tcount 6.477>ttable 2.004 and the Motivation variable has a positive and significant effect on employee performance where it can be seen tcount 11.166>ttable value 2.004. Then simultaneously (F test), the F value is 83.947> F table 3.16. So that workload and motivation have a positive and significant effect on employee performance at PT. Mandiri Abadi Permai. The results of the coefficient of determination for the Adjusted R square value are 0.744 (74.4%). So it can be said that 74.4% of the variation in the independent variables in workload and motivation contributes to employee performance variables at PT. Madiri Abadi Permai, while the remaining 25.6% is influenced by other variables outside the model.
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