ANALISIS KINERJA BANK METODE RGEC PT. BPR BANK BOYOLALI (PERSERODA) Periode Tahun 2021 – 2023
Bibliographic record
Abstract
A bank is a financial intermediary institution, generally established with the authority to accept money deposits, lend money, and issue promissory notes or known as banknotes. Financial performance is one of the important indicators to determine the financial condition of the bank. The better the financial performance, the better or healthier the health level of the bank. (Sukarno, 2011: 2). This study aims to analyze banking health performance using the RGEC method. The financial ratios used in this study are LDR, CGC, ROA, BOPO, and CAR. The research object in this study is the financial performance report of PT BPR Bank Boyolali using the RGEC method for the final quarter period of 2021 - 2023. This type of research is descriptive quantitative, a research method that utilizes quantitative data and is described descriptively. This study uses secondary data in the form of financial information obtained from financial reports published through the Financial Services Authority (OJK) website. The results of this study indicate a decrease in the LDR ratio from 98% in 2021 to 79.9% in 2023, reflecting a more balanced management of loans and deposits. The implementation of Good Corporate Governance (GCG) principles remains good with high regulatory compliance. Profitability remains solid with a stable ROA at 2.5% in 2021 and 2022, albeit slightly declining to 2.3% in 2023, and an efficient BOPO ratio of 79.9% in 2021.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 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".