Analisis Determinan Tingkat Pertumbuhan Total Aset Perbankan Syariah di Indonesia
Bibliographic record
Abstract
Total assets of sharia banking in Indonesia ranked the 9th largest Islamic banking assets in the world with a total asset value of USD 37.7 billion and contributed 6.1% market share in the 3rd quarter of 2020. Despite that, the growth of Islamic banking assets experienced a slowdown from 2016 to 2020. Accordingly, it is important to identify critical factors for the growth of Islamic banking assets to accelerate the growth of the industry. This study examines the determinants of the growth of sharia banking assets which are represented by internal variables of TPF, FDR, and CAR, and external variables of GDP, Inflation, and BI Rate using the Error Correction Model (ECM) approach with secondary data samples from all BUS and UUS in Indonesia. The results showed that in the long term and short term, TPF and FDR variables have a positive and significant effect on the total assets of sharia banking, while the CAR and Inflation variables have a positive and insignificant effect, and the GDP and BI Rate variables have a negative and insignificant effect.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".