Restorative Justice dalam Tindak Pidana Pembunuhan: Perspektif Hukum Pidana Indonesia dan Hukum Pidana Islam
Bibliographic record
Abstract
The completion of the homicide in Indonesia did’nt have effectiveness, both in order to give a deterrent effect and the creation of the security and peace in society. Conventional punishment process, as applicable in Indonesia, didn’t give space to the parties (the victim, offender, and community ) involved to participate actively in solving their problems. Position of the State was too dominant, thus denying the people's participation in law enforcement. Imprisonment system adopted in Indonesian criminal law also didn’t provide a comprehensive solution. Retributive justice approach adopted by the Indonesian criminal law needs to be reformed and replaced with a restorative justice. Restoration is an alternative approach to solve crime that emphasized on recovery conflicts and rebulid balances in society. This approach has been also applied in many countries, both of which adopted the system of criminal law and civillaw (France, Germany, the Netherlands), or apply the common law system of criminal law (United States, Canada, Australia). This approach is already practiced in Islamic criminal law, namely the law of qisas. In completion of murder, procedure of Qisas involving all parties, namely the victim, offender and community. Family of victim have the right to determine the punishment, whether qisas (killed), or diyat (pay a fine), or give forgiveness to the offender . The existence of three alternative penalties and engagement of the litigants shows that Islamic criminal law applying restorative justice approach. Position of Sultan (the State) is a mediator as well as a supervisor in law enforcement. Completion of this approach is able to resolve crimes with rebuilding relations after the criminal act.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".