ANALISIS Z-SCORE DALAM MENGUKUR KINERJA KEUANGAN UNTUK MEMPREDIKSI KEBANGKRUTAN PERUSAHAAN MANUFAKTUR PADA MASA PANDEMI COVID-19
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A manufacturing company is a business entity whose main activity is to process raw materials into finished goods, therefore they have a sale value. During the covid-19 pandemic, many manufacturing companies were threatened with bankruptcy. That is because the company’s performance has decreased. The purpose of this research is to compare how big the opportunities of PT. Astra International, PT. Mandom Indonesia, PT. Gudang Garam, and PT. Sri Rejeki Isman bankruptcy as a result of covid-19 by using the Altman z-score model. Financial distress is a situation where a company experiences liquidity difficulties or the ability to fulfill its obligations. Based on the results of PT. Astra International from 2016 to 2020 in the first quarter was potentially bankruptcy, while in the second quarter the company was based on the grey area. PT. Mandom Indonesia both in the first quarter and second quarter in healthy. PT. Gudang Garam in first quarter and second quarter in the grey area. PT. Sri Rejeki Isman in the first quarter and second quarter classified as a potentially bankrupt company.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it