Analisis Mekanisme Corporate Governance Terhadap Potensi Kesulitan Keuangan (Financial Distress) Perusahaan Publik - Putri, Rumanintya Lisaria; Yanti, Dyah Agustin Widhi; Mahmud, Mahmud (JURNAL APLIKASI PELAYARAN DAN KEPELABUHANAN, 2019)
This study aims to determine the mechanism of corporate governance (independent commissioners, managerial ownership, institutional ownership, audit committee and audit quality) affect the potential financial distress (financial distress) of public companies. The research method used is multiple linear regression with the classic assumption test, and hypothesis testing that produces the following analysis: F value in the calculated statistics is 11.731 and a sig value of 0.014 because α> 0.014 means that significant Ho1 is rejected and Ha is accepted. The results of the study prove that the mechanism of corporate governance influences the financial distress potential of public companies. The results show that the independent commissioner (tcount of -3,139. This value is greater than ttable -2,500) has a statistically significant effect on the potential for financial difficulties. T test results indicate that managerial ownership (has a t-value of -4.236. This value is smaller than t table 2.500) statistically significant effect on the potential for financial difficulties. T test results show that institutional ownership (has a tcount of 2.747. This value is greater than t table 2.500) statistically has a significant effect on the potential for financial difficulties. T test results show that the audit committee (has a t-count of -2,615. This value is smaller than the table -2,500) has a statistically significant effect on the potential for financial difficulties. T test results indicate that audit quality (has a tcount of 7.426. This value is smaller than t-table 2,500) statistically has a significant effect on the potential for financial difficulties. The coefficient of determination shown from the adjusted R2 value of 0.054 means that 5.4% of the variation in potential financial difficulties can be explained by the 5 predictors used in this study, while the remaining 94.6% of the potential financial difficulties can be explained by other variables.