PENGARUH RISIKO LIKUIDITAS, RISIKO KREDIT, RISIKO PASAR DAN RISIKO OPERASIONAL TERHADAP RETURN ON ASSETS (ROA) PADA BANKUMUM SWASTA NASIONAL DEVISA
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
The Study Entitled Business Risk Influence Toward ROA ( Return On Asset ) In The Foreign Exchange National Private Banks Go Public. In this study aims to determine whether the LDR, IPR, NPL, IRR, BOPO, and FBIR have a significant impact on ROA jointly and individually for state banks in the beginning of the period first quarter 2010 to fourth quarter year 2013. Data and data collecting method used in this research is secondary data source from quarterly financial statement from Foreign Exchange national private banks go public Financial statement appendix researched from quarterly financial statement I 2010 until quarterly financial statement IV 2013. Data analysis technique used in this research in regression analysis, F-test and T-test.Use of the analysis carried out for the steps in calculating financial ratios and analysis to test the hypothesis. Based on the calculation result known that the LDR, IPR, NPL, IRR, BOPO and FBIR, jointly simultan in the Foreign Exchange National Private Banks Go Public Key Words:Banking business risk, Regression analysis, Business Risk Influence Towards ROA.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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