PENGARUH BI RATE, INFLASI DAN KURS TUKAR TERHADAP PERFORMA LIKUIDITAS PERBANKAN KONVENSIONAL DI MASA PANDEMI COVID-19
Bibliographic record
Abstract
The liquidity ratio is a metric that measures a bank’s capacity to meet short-term obligations and repay money disbursed when they are due. The goal of this study is to examine the performance of conventional banking liquidity during the covid-19 pandemic, as well as the impact of the BI rate, inflation and exchange rate variables on conventional banking liquidity. Secondary data from public reports on the websites of the Financial Services Authority (OJK), Bank Indonesia (BI), the Central Statistics Agency (BPS), and the Ministry of Trade from the first quarter of 2020 to the first quarter of 2021 was used in this study. Method The analysis used in this study uses panel data regression analysis. The result of this research is that the BI rate variable has a positive and significant effect on liquidity. Inflation and Exchange Rate variables have a negative and significant effect on liquidity.
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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 | 0.002 | 0.001 |
| 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".