Pengaruh Motivasi dan Lingkungan Kerja Terhadap Kinerja Karyawan Kompartemen Sekretariat Perusahaan & Tata Kelola PT Pusri Palembang dengan Disiplin Kerja Sebagai Variabel Intervening

The study aims to determine the Influence of Motivation and Work Environment on Employee Performance in the Corporate Secretariat Compartment & Governance of PT Pusri Palembang with Work Discipline as an Intervening Variable. The population of this study was 42 people. Data analysis used in this study is the Structural Equation Model (SEM) analysis method operated through the Partial Least Square (PLS) program. The results of the study indicate that there is an Influence of Motivation and Work Environment on Employee Performance in the Corporate Secretariat & Governance Compartment of PT Pusri Palembang with Work Discipline as an Intervening Variable with the equation Y = 0.419x1 + 0.407x2 + ε1 and the equation Z = 0.244x1 + 0.142x2 + 0.665Y + ε2 there is an influence of Motivation on Work Discipline indicated by the equation of the t-statistic value of 2.545> 1.960 and p-values ​​of 0.011 <0.05, the Work Environment has a significant effect on Work Discipline indicated by the t-statistic value of 2.492> 1.960 and p-values ​​of 0.013 <0.05, Motivation has an effect on Employee Performance indicated by the t-statistic value of 2.534> 1.960 and p-values ​​of 0.012 <0.05, Work Environment affects Employee Performance indicated by t-statistics of 2,289> 1,960 and p-values ​​of 0.022 <0.05, Work Discipline affects Employee Performance with t-statistics of 7,584> 1,960 and p-values ​​of 0.000 <0.05. The R2 value for the latent variable Work Discipline of Work Discipline as a mediating variable is 0.541, which means that the value identifies that variations in employee Work Discipline can be explained by exogenous latent variables (Motivation and Work Environment) of 54.1% while the remaining 45.9% is explained by other variables. The R2 value for the latent variable Employee Performance is 89.7% while the remaining 10.3% is explained by variables not included in the study. The larger the R-square number indicates that the greater the independent variable can explain the dependent variable, so the better the structural equation.