Kriminalisasi dalam Tindak Pidana terhadap Penetapan Hasil Pemilihan Umum
Bibliographic record
Abstract
ABSTRACT: The stages of determining election results have important characteristics; because it determines the party who wins the election and, at the same time, proves the legality and legitimacy of holding the election. Nevertheless, there are various problems regarding the formulation of policies in criminal acts related to the determination of election results. This research on the formulation of criminal acts associated with election results is normative research with a statutory approach, a conceptual approach, and a comparative approach. This legal research aims to discuss the formulation of the crime of 'late setting election results' and 'not determining election results; while at the same time reviewing future projections by formulating an ideal formulation regarding the formulation of the criminal act of determining election results. The results of the study state that the formulation of criminalization policies in illegal acts related to the determination of election results is regulated to meet various legal problems, including the dimensions of action, the dimensions of criminal responsibility, and the dimensions of criminal sanctions. Then, by taking references from Canada and Kenya, the projections of the formulation are prepared by specifying two objects of action, namely the act of not determining the election results and the act of being late in determining the election results as a crime. Completing the formulation was followed by a complete determination of the subject of a criminal offense accompanied by intentional errors and the formulation of flexibility-based sanctions oriented to avoiding sentencing disparities.
 KEYWORDS: Criminalization, Criminal Act, Determination of General Election Result
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".