HUBUNGAN CORPORATE GOVERNANCE DENGAN KINERJA KEUANGAN DAN KINERJA SAHAM PERUSAHAAN (Studi Empiris Pada Perusahaan Yang Terdaftar Pada BEI)
Bibliographic record
Abstract
Corporate Governance menurut Organization for Economic Cooperation and Development (OECD) mengacu kepada pembagian kewenangan antara semua pihak yang menentukan arah dan performance suatu perusahaan. Pengukuran corporate governance diukur dengan menggunakan Corporate Governance Perception Index (CGPI). Corporate Governance Perception Index (CGPI) merupakan riset penerapan good corporate governance pada perusahaan public yang tercatat di Bursa Efek Indonesia. Penelitian ini bertujuan untuk mengetahui hubungan antara perusahaan yang menerapkan corporate governance dan berpartisipasi dalam Corporate Governance Perception Index dengan kinerja keuangan dan kinerja saham pada perusahaan yang terdaftar di Bursa Efek Indonesia. Data yang digunakan yang dalam penelitian ini adalah perusahaan finansial dan non finansial yang sudah menerapkan corporate governance di Bursa Efek Indonesia dengan mengikuti survei CGPI tahun 2007 sampai tahun 2009. Hasil penelitian ini menunjukkan penerapan corporate governance pada sampel perusahaan finansial dan non finansial yang terdaftar pada Bursa Efek Indonesia pada tahun 2007-2009 mempunyai hubungan dengan kinerja keuangan perusahaan, baik kinerja pasar maupun kinerja operasional (Tobin’s Q dan ROE) serta mempunyai hubungan dengan kinerja saham (RETH). Semakin terpercaya suatu perusahaan maka nilai CGPI semakin tinggi maka semakin baik pula kinerja keuangan maupun kinerja saham suatu perusahaan. Kata Kunci: CG,CGPI, Kinerja Keuangan Perusahaan, Kinerja Saham Perusahaan
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".