The Effect of Good Corporate Governance and Internal Audit Implementation of Quality of Financial Statement through Intellectual Capital in Pt Jakarta Tourisindo
Bibliographic record
Abstract
This study aims to: 1) test and analyze the effect of the implementation of good corporate governance influence intellectual capital at PT Jakarta Tourisindo, 2) test and analyze the effect of internal audit on intellectual capital at PT Jakarta Tourisindo, 3) test and analyze the effect of the application of good corporate governance affect the quality of financial statements at PT Jakarta Tourisindo, 4) test and analyze the effect of internal audit affect the quality of financial statements at PT Jakarta Tourisindo, 5) test and analyze the effect of intellectual capital affect the quality of financial statements at PT Jakarta Tourisindo and 6) test and analyze the effect of the implementation of good corporate governance and internal audit affect the quality of reports through intellectual capital at PT Jakarta Tourisindo. The study was conducted at PT Jakarta Tourisindo with a sample of 100 respondents. The sampling technique uses a random sampling technique. The method of data analysis uses descriptive analysis and path analysis. The results showed that: 1) there was a positive and significant effect between good corporate governance on intellectual capital, 2) there was a positive and significant effect between internal audit on intellectual capital, 3) there was a positive and significant effect between the application of good corporate governance on the quality of financial statements, 4) there is no positive and significant influence between internal audit on the quality of financial statements, 5) there is no positive and significant influence between intellectual capital on the quality of financial statements, and 6) there is a positive and significant effect between good corporate governance and internal audit on quality financial statements through intellectual capital.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".