Pengaruh Perekonomian Indonesia di Berbagai Sektor Akibat Corona Virus Disease 2019 (Covid-19)
Bibliographic record
Abstract
Pengaruh Perekonomian Indonesia di Berbagai Sektor Akibat Corona Virus Disease 2019 (Covid-19). This research was carried out based on the covid-19 outbreak that is currently happening in Indonesia and in several countries. This pandemic is not only threatening public health and safety but also threatens the economic situation in various sectors. The research method used in this research is qualitative research, data collection techniques used in this study are library research techniques. Based on the results of the Bank Indonesia (BI) Business Activity Survey (SKDU) in Quarter I-2020 indicating a decline in the economy in various sectors. This can be seen from the Weighted Net Balance (WNB) value in the first quarter of 2020 amounting to -5.56%, which is quite deep compared to 7.79% in quarter IV-2019. The decrease was caused by the decrease in demand and supply due to co-19.
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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 | 0.000 | 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) | 0.007 | 0.002 |
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".