Analisis Pangaruh Asset Growth, Total Asset Turnover, Firm Size, Operating Leverage, Dan Financial Leverage Terhadap Beta Saham (StudiKasusPerusahaan Finansial yang terdaftar di Bursa Efek Indonesia Periode 2013-2016)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Penelitian ini bertujuan untuk memperolah bukti secara empiris pengaruh, Asset Growth, Total Asset Turnover, Firm Size, Operating Leverage , dan Financial Leverage terhadap Beta Saham (Studi Kasus Perusahaan Finansial yang terdaftar di Bursa Efek Indonesia Periode 2013-2016).Berdasarkan purposive sampling diperoleh 28 pada Perusahaan Finansial di Bursa Efek Indonesia (BEI) sebagai sampel dalam penelitian ini dan periode pengamatan dari tahun 2013 sampai tahun 2016. Dalam pemecahan masalah peneliti memakai uji asumsi klasik dan uji hipotesis dengan analisa regresi berganda. Hasil perhitungan, pengujian, dan pembahasan membuktikan bahwa Asset Growth, Total Asset Turnover, Operating Leverage, dan Financial Leverage berpengaruh positif dan Signifikan terhadap Beta Saham,sedangkan Firm Size berpengaruh negatif dan Signifikan terhadap Beta Saham. Kata kunci :Beta Saham, Asset Growth, Total Asset Turnover, Firm Size, Operating Leverage , dan Financial Leverage
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 it