Penegakan Hukum terhadap Guest House dan Villa tanpa Izin di Kabupaten Badung
Bibliographic record
Abstract
Tourism is a source of local revenue and its investment is a potentially vital production factor in the service production business in this field. To support tourism accommodation in the tourist area of Badung Regency, guest houses (boarding houses/rented houses) and villas are needed as support. Especially in Badung Regency, in the Canggu area, many houses are used as guest houses for guests who want to stay in Bali. This study aims to determine the supervision of Guest Houses and Villas in Badung Regency, and to determine the application of sanctions against guest houses and villas that violate permits in Badung Regency. The method in this research is a type of normative legal research which is carried out with the method of recording and reviewing based on legal materials. In this study, studying and gathering information through legal science books without deviating from positive law in order to form a conclusion. The research results show that the supervision of Guest Houses and Villas in Badung Regency is given the authority by the Regional Regulation through the Civil Service Police Unit which is assigned to monitor every building that does not have a permit in the Badung Regency area, especially in the Canggu area. Then, sanctions against violators are in the form of warnings 3 times, if they do not disobey the villa owner, they will be subject to forced demolition by officers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 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".