Internal and External Factors that Influence Non-Performing Financing in Sharia Commercial Banks
Bibliographic record
Abstract
Problematic financing is reflected in Non-Performing Financing (NPF) because NPF is a parameter that can determine whether there is risky financing in Islamic banking. This research aims to determine the impact of Capital Adequacy Ratio (CAR), Operating Expenses and Operating Income (BOPO), inflation, and Bank Indonesia (BI) rates on Non-Performing Financing (NPF) in Sharia Commercial Banks in Indonesia. The data in this research uses secondary data. The population used is Sharia Commercial Banks registered with the Financial Services Authority (FSA) in 2018-2022. The sample used is the published report for the 2018-2022 quarter I-IV period. The research results show that BOPO has a positive and significant impact on NPF. Meanwhile, CAR, inflation, and BI rates have no significant impact on NPF.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".