Perlindungan Konsumen terhadap Kelangkaan Produk Non Pokok Akibat Penimbunan yang Dilakukan oleh Pelaku Usaha
Bibliographic record
Abstract
In 2020 Walls Indonesia re-launched their legendary product, "Viennetta" Ice Cream which was famous in the 90s. but this is misused by bad people who are not responsible for their own interests. They took advantage of the public's enthusiasm for the return of the legendary product from Walls Indonesia, namely Viennetta Ice Cream by hoarding these items and selling them at a higher price. The regulations regarding consumer protection against hoarding of goods have received protection from the Ministry of Trade in the Regulation of the Minister of Trade Number 20/M-DAG/PER/3/2017 concerning Registration of Business Actors in the Distribution of Staple Needs, but unfortunately this regulation only applies to basic goods. Therefore, this study aims to educate consumers in order to know their rights as consumers and so that the government can re-discuss regulations regarding stockpiling of goods so that they can be expanded not only to basic necessities by using the juridical normative research method and using a statutory approach, the authors get the results of this research that consumers can still get legal protection against the scarcity of a non-basic item by using the Trade Law, the Consumer Protection Law, and the Business Competition Law..
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".