DAMPAK PANDEMI COVID-19 TERHADAP KONTRIBUSI NILAI PERDAGANGAN INDONESIA-CHINA (CATRUWULAN I TAHUN 2020)
Bibliographic record
Abstract
The background of this research is the decline the value of exports from China to countries in Asia including Indonesia due to the Covid-19 pandemic since December 2019. Indonesia has imposed import restrictions on certain products from China to minimizing the spread of the Covid-19 virus. The purpose of this study is to analyze the value of Indonesia-China trade in the first quarter of 2020. The research method used was a descrptif quantitative with the main data being the value of exports and imports between Indonesia and China obtained from data from the Indonesian Central Statistics Agency. The results of the study of the data obtained, that trade between Indonesia and China still provides a fairly large contribution value to Indonesia's foreign trade. This contribution is expressed as a percentage of Indonesia's total exports to China and imports from China to Indonesia. The recommendation based on the results of this study is that Indonesia-China trade should be maintained because China is the main trading partner country to maintain the continuity of Indonesia's economy
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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 | 0.000 | 0.000 |
| 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) | 0.009 | 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".