Biaya Promosi dan Penghimpunan Dana Pihak Ketiga Pada Bank Pembiayaan Rakyat Syariah
Bibliographic record
Abstract
The aim of this study is to analyze whether there is influence the expense of promotion is issued to against amount of third party assembled by BPRS. In addition, to analyze the variable lag time (lag) cost of promotion that the most effective effect on changes in third party funds obtained by BPRS. This study used regression analysis or AutoRegressive Distributed Lag (ARDL). The variables used are promotion cost as independent variable and third party fund as dependent variable. The result of this study showed that the amount of promotion cost has a positive and significant influence on the increasing amount of third party funds of BPRS, as explained by the results of ARDL analysis conducted by the author, that is change in third party funds affected by third party funds one quarter earlier and influenced by the amount of promotional costs the previous quarter or 15 months earlier. This indicates that the higher the promotion expense of budget, the BPRS will be able to collect more third party funds.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".