Kinerja Keuangan Sebelum Dan Saat Pandemic Covid-19 Pada Perusahaan Telekomunikasi Yang Tercatat Di Bursa Efek Indonesia
Bibliographic record
Abstract
The purpose of this study was to determine differences in the financial performance of telecommunication companies listed on the Indonesia Stock Exchange before and during the COVID-19 pandemic. The method in this research uses descriptive quantitative. The sampling technique was carried out by purposive sampling. The type of data used is secondary data obtained from the Indonesia Stock Exchange in the form of financial reports for the first quarter - fourth quarter of the Telecommunication Sector Company for the period 2018 and 2020. The research variables used are Current Ratio, Net Profit Margin, Return On Assets, Debt to Asset Ratio and Debt to Equity Ratio. The results of this study indicate a significant difference in the Current Ratio and Debt to Asset Ratio While the Net Profit Margin, Return On Assets and Debt to Equity Ratio there are no significant differences
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".