Dampak Pandemi Covid-19 terhadap Pendapatan Sektor Penyediaan Akomodasi dan Makan Minum Provinsi Bali
Bibliographic record
Abstract
The Covid-19 pandemic has caused a decline in the economy in Indonesia. This also happened in Bali, especially in the accommodation and food service sector which is one of the largest contributors to the GRDP of Bali Province. Therefore, this study aims to find out how and how big the impact of the Covid-19 pandemic on the sector of providing accommodation and food and drink. This study uses an intervention analysis method with a step function. The results of the study show that the Covid-19 pandemic has a significant direct impact on the GRDP of this sector, which is 15.22 percent. The worst impact occurred in the third quarter of 2021, which was 48.58 percent. The impact of the Covid-19 pandemic on the GRDP of the permanent accommodation and food and beverage sector until the end of 2021. This research is expected to be able to help the government and related sector business actors to take actions that are expected to reduce the impact of the Covid-19 pandemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".