Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Pusat Publikasi Ilmu Manajemen
Faisal Yudha
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
The Influence of Motivation, Discipline and Work Environment on the Performance of Afdeling 1 PTPN IV Regional III Kebun Sei Galuh Employees. Ferisca Nurwidyanti; Faisal Yudha
PPIMAN Pusat Publikasi Ilmu Manajemen Vol. 2 No. 3 (2024): Juli : Pusat Publikasi Ilmu Manajemen
Publisher : Fakultas Ekonomi & Bisnis, Universitas Nusa Nipa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59603/ppiman.v2i3.491

Abstract

The aim of this research is to determine the influence of Motivation, Discipline and Work Environment on employee performance at PTPN IV Regional III Kebun Sei Galuh. The sample in this study was 45 employees of Afdeling 1 PTPN IV Regional III Kebun Sei Galuh. Based on the research results, the correlation value (R) is 0.934. This figure shows that there is a strong link between the independent variable and the dependent variable at PTPN IV Regional III. Meanwhile, the R Square value is 0.872, which shows that Motivation, Work Discipline and Work Environment as a whole have an effect of 87.2% on the performance of PTPN IV Regional III employees. Partially motivation with a significance value of 0.013 is smaller than alpha 0.05. So motivation has a significant effect on the performance of Afdeling I PTPN IV Regional III Kebun Sei Galuh employees. Work Discipline with a significance value of 0.038 is smaller than alpha 0.05. Simultaneously, with a significance of 0.000 which is smaller than alpha 0.05, it means that the variables Motivation, Work Discipline and Work Environment simultaneously have a significant effect on the performance of Afdeling I PTPN IV Regional III Kebun Sei Galuh employees. The multiple linear regression equation is as follows: Y = 0,984 + 0,299X1 + 0,241X2 + 0,402X3 + ε
Co-Authors Ferisca Nurwidyanti