ANALISIS EFISIENSI BANK UMUM SEBELUM DAN SETELAH KRISIS EKONOMI 2008 DENGAN MENGGUNAKAN METODE NON PARAMETRIK DATA ENVELOPMENT ANALYSIS (DEA)
Bibliographic record
Abstract
The economic crisis that occurred in quarter IV of 2008 until the quarter II 2009 which took place in the world including Indonesia handy, have resulted in a variety of global financial institutions suffered losses and bankruptcy. Bankruptcy that plagued banks-banks in Indonesia is affected by bank accepted deposits increased, while loans provided decreased, leading to increased interest on loans given to banks. Population research used are commercial banks listed on the IDX (Indonesia stock exchange) period 2006-2012. This study used the method of DEA (Data Envelopment Analysis) and test different ANOVA. The results of hypothesis testing with different ANOVA test showed the presence of tidal differences in the efficiency of banking performance before and after the economic crisis. The results can provide advice to companies banking on anticipated at the time of the crisis, bank indonesia concerning the banking performance evaluation andimplementation of the industrial policy of banks, borrowers, investors, banks and stockholders about the banking efficiency information at the time of the crisis.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".