FAKTOR FAKTOR YANG MEMPENGARUHI TABUNGAN MUDHARABAH PADA BANK UMUM SYARIAH (BUS) DI INDONESIA TAHUN 2018 – 2019
Bibliographic record
Abstract
This study aims to examine and analyze the factors that affect the amount of easy-to-use savings savings. Thesefactors are the Profit Sharing Rate, Liquidity, Bank Size and Number of Bank Offices. The object of this research is all Islamic Commercial Banks (BUS) that report their Financial Statements to the Monetary Services Authority, with an observation period for the first quarter of 2018 to the fourth quarter of 2019. The sampling method uses the Census method, namely the entire available population is sampled and there are 14 Sharia Commercial Banks. Data analysis using multiple linear regression. The results of the study found that the Profit Sharing Rate has no effect, Liquidity has a significant negative effect, while the Bank Size and Number of Bank Offices have a significant positive effect on the Total Mudharabah Deposits.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".