Optimizing Smart Governance to Enhance Smart City Implementation and Employee Productivity

Abstract

This study aims to find out how smart governance influences to create a smart city on employee work productivity at the Governor's Office of North Sumatra. In this study, the authors used quantitative research methods. Data collection procedures in this study are observation (observation), interviews, documentation studies and questionnaires. Data analysis techniques in this study were correlation analysis, simple linear regression analysis, hypothesis testing (t test), and coefficient of determination test (R2). The results of the correlation test obtained that the correlation coefficient between variable X (Smart Governance) and variable Y (Employee Work Productivity) is 0.730. This means that variables X and Y have a strong influence because they have a correlation value that is at 0.60 – 0.799 (strong/high correlation). The results of simple linear regression coefficient calculations obtained a constant coefficient value of 3,084 and an independent variable coefficient (X) of 0,827 so that a regression equation Y = 3,084 + 0,827 X + ? or Employee Work Productivity = 3,084 + 0.827 Smart Governance + ?. The results of calculations with the t test (hypothesis) obtained a calculated t value of 8.614 which is greater than the t table value of 1.997 or 8.614 > 1.997 at a sig level of 0.000. So, the test results conclude that there is a positive and significant influence between variable X on variable Y, or in other words Smart Governance (X) has a positive and significant effect on Employee Work Productivity (Y) in the Office of the Governor of North Sumatra in the General Affairs and Equipment Bureau section. The test results using the coefficient of determination, obtained an R value of 0.730 while an R2 value of 0.533 means a coefficient of determination of 0.533 or R2 x 100% of 53.3%. That is, this value has implications that the influence of the Smart Governance (X) variable affects Employee Work Productivity (Y) at the North Sumatra Governor's Office by 53.3% and the remaining 46.7% is influenced by other variables not discussed in the study