Analisis Financial Distress Untuk Memprediksi Potensi Kebangkrutan PT. X Yang Terdaftar Di BEI
Bibliographic record
Abstract
Financial distress can occur in every company. If financial distress is not immediately addressed, it can lead to bankruptcy. This study aims to determine the potential for bankruptcy at PT. X is listed on the Indonesia Stock Exchange (IDX) using the Springate model, the Zmijewski model and the Grover model. The method used is a qualitative method. The research sample is a statement of financial position and profit and loss of PT. X the first quarter of 2021 - the first quarter of 2022. The results of the research from the three models used are only the Springate model which predicts the company in a potentially bankrupt condition, while the Zmijewski model and the Grover model predict the company in a non-bankrupt potential condition. Keywords: Financial Distress; Springate Model; Zmijewski Model; Grover Model
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.006 | 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".