ANALISIS FAKTOR INTERNAL DAN EKSTERNAL YANG MEMPENGARUHI NON PERFORMING LOAN PADA BANK CAMPURAN DI INDONESIA (PERIODE 2012-2017)
Bibliographic record
Abstract
Abstract This study aims to determine the effect of external factors by using BI Rate, Inflation, Gross Domestic Product (GDP), Exchange Rate and Internal Factors using Capital Adequacy Ratio (CAR), Loan Deposit Ratio (LDR) Return on Assets (ROA), Interest Rate Spread (IRS) Against Non Performing Loans (NPLs). Sampel selection method in this study using purposive sampling. Selected Sampel there are 10 banks from 15 Mixed banks in Indonesia. The data used is quarterly data, from the first quarter of 2012 to second quarter of 2017. The results show that Capital Adequacy Ratio, Inflation, and Gross Domestic Product growth have no significant effect on Non Performing Loan, while Loan Deposit Ratio, Return On Asset, Interest Rate Spread, BI Rate, and Exchange Rate have a significant effect on Non Performing Loan. On the other hand, external factors, internal factors simultaneously have a significant influence on the Non Performing Loan. Keywords : loan deposit ratio, return on asset, interest rate spread, capital adequacy ratio
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.001 |
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".