ANALISIS PREDIKSI KEBANGKRUTAN MODEL ZMIJEWSKI DAN MODEL OHLSON PADA BADAN USAHA MILIK NEGARA (BUMN) YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) PERIODE 2014 – 2018
Bibliographic record
Abstract
The purpose of this research is to analyze the most accuratebankruptcy prediction model between the Zmijewski and Ohlson models inpredicting the bankruptcy of BUMN companies listed on the IDX on 2014 to 2018.The sample used is 16 BUMN with purposive sampling method. The data analysismethod uses the Zmjewski model and the Ohlson model with the help of MicrosoftExcel 2010. The results of this study are the Zmijewskizmodel is the most accuratemodelzin predicting bankruptcyzof BUMN companies listedzon thezIDX for the2014-2018 periodzwith an accuracy rate of 60% and type error. 40% while theOhlson model has an accuracy rate of 16.25% and a type error of 83.75%.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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".