Pertanggungjawaban Penyidik Terhadap Korban Salah Tangkap Tindak Pidana (Studi Kasus Nomor 10/Pid.Pra/2024/PN Bdg)
Bibliographic record
Abstract
Kasus salah tangkap sebenarnya sudah menjadi hal umum didengar oleh Masyarakat Indonesia, dari kasus ini berdasarkan Putusan Studi Kasus Nomor 10/Pid.Pra/2024/PN BDG harus ada pertanggungjawaban sesuai dengan peraturan perundang-undang di KUHAP Pasal 95 ayat (1) tentang ganti rugi, Pasal 333 Ayat (1) akan adanya disiplin hal ini bertujuan Untuk mengetahui dan menganalisis pertanggungjawaban penyidik dan perlindungan hukum terhadap korban salah tangkap, analisis ini akan menggunakan penelitian yuridis normative dengan menggunakan pedekatan masalah perUndang-Undang, konseptual, studi kasus dan komparatif, sehingga dari hasil analisis ini adalah lemahnya Lembaga Independen diindonesia yang hanya dari Lembaga Internal saja tidak ada Lembaga eksternal seperti yang telah diterapkan oleh negara Canada yang memiliki Lembaga Eksternal Independen dengan adanya Lembaga LECA yang didirikan pada Tahun 2024 sehingga meminimalisir adanya salah tangkap, dan kepastian hukum.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".