Ramdhany, Denny
Unknown Affiliation

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

Found 1 Documents
Search

Pengaruh Perencanaan Kerja, Risk Management, dan Good Governance Terhadap Kinerja Pegawai (Studi Pada Direktorat Jenderal Bina Keuangan Daerah, Kementerian Dalam Negeri) Ramdhany, Denny; Maulina, Anita
Neraca : Jurnal Akuntansi Terapan Vol. 6 No. 2: April 2025
Publisher : Institut Ilmu Sosial dan Manajemen Stiami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31334/neraca.v6i2.4790

Abstract

In an effort to create a professional government bureaucracy with characteristics, integrated, high-performance, capable of serving the public, neutral, prosperous, dedicated, and upholding the basic values and code of ethics of the state apparatus, bureaucratic reform is implemented in government agencies. The existence of bureaucratic reform demands improvements in various aspects of governance. This study aims to determine the effect of work planning (X1), risk management (X2) and good governance (X3) on employee performance (Y), especially at the Directorate General of Regional Financial Development of the Ministry of Home Affairs. The type of research used in this research is quantitative research with descriptive analysis methods. The population in this study were all employees of the Directorate General of Regional Finance with a sample of 76 people. The results showed that work planning has a significant influence on employee performance, with a contribution of 26.5%, risk management also has a significant influence on employee performance, with a contribution of 36.6%, good governance shows the greatest influence on employee performance, with a contribution of 64.6%. While work planning, risk management, and good governance together have an influence of 65.8%, the remaining 34.2% is explained by other variables not included in the regression model. While work planning, risk management, and good governance together have an influence of 65.8%, the remaining 34.2% is explained by other variables not included in the regression model.