Analisis pengaruh dana pihak ketiga dan pembiayaan perbankan syariah terhadap pertumbuhan ekonomi Indonesia tahun 2011-2021
Bibliographic record
Abstract
As a financial institution, banks have a crucial role in the Indonesian economy to improve people's living standards through the intermediation function in raising funds from the community and channeling funds to the community. This function in Islamic banking is carried out with third-party funds and financing. The purpose of this study is to find out the influence of third-party funds and Islamic banking financing on Indonesia's economic growth. This research uses a quantitative approach using secondary data (time series), namely third-party fund data and financing, namely mudharabah financing, musyarakah, murabahah, istishna', and qard from Islamic Banking Statistics by OJK and Gross Domestic Product data by BPS from the first quarter of 2011 to the second quarter of 2021. Researchers used the Error Correction Model (ECM) analysis technique in the analysis. The results of this study are variables that affect economic growth in the long term: mudharabah financing and musyarakah, while in the short term is mudharabah financing. Variable third-party funds, murabahah, istishna' and qard do not affect economic growth in the short and long term.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.007 | 0.002 |
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".