Tindak Pidana Penerbangan: Studi Terhadap Penyampaian Informasi Palsu Yang Membahayakan Keselamatan Penerbangan Pada Putusan Nomor 43/PID.B/2018/PN LBJ
Bibliographic record
Abstract
Aviation safety, which is a vital aspect of air transportation, is now facing a serious threat due to the spread of false information, thus requiring strict law enforcement as regulated in Article 437 of Law Number 1 of 2009, one example of which can be seen through Decision Number 43/Pid.B/2018/PN Lbj. This study aims to analyze criminal liability for the dissemination of false information that endangers aviation safety, as regulated in Article 437 of Law Number 1 of 2009, using the case study of Decision Number 43/Pid.B/2018/PN Lbj as an effort to understand the application of criminal law in addressing the challenges of non-conventional crimes in the air transportation sector. This research uses a normative juridical method with a descriptive-analytical approach, relying on secondary data in the form of Decision Number 43/Pid.B/2018/PN Lbj and analyzed qualitatively through library research to examine criminal liability for the dissemination of false information that endangers aviation safety. The research results state that the Panel of Judges in the Decision of the Labuan Bajo District Court Number 43/Pid.B/2018/PN Lbj has carefully considered and legally and convincingly proven all elements of the criminal act of disseminating false information that endangers aviation safety, namely the element of “every person” which refers to Article 344 letter e jo. Article 437 paragraph (1) of Law Number 1 of 2009, criminal law doctrines, and expert testimony; the element of “disseminating false information” which is proven through witness testimony, the defendant’s confession, as well as international standards under ICAO Annex 17; and the element of “endangering aviation safety” which is supported by positive legal norms, international security standards, and legal expert doctrines, thereby declaring the defendant MARIA DO ROSARIO DO SANTOS RODRIGUES legally proven guilty.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".