PERTIMBANGAN HAKIM DALAM MENJATUHAN HUKUMAN PIDANA BAGI ANGGOTA TENTARA NASIONAL INDONESIA YANG MELAKUKAN TINDAK PIDANA DESERSI
Bibliographic record
Abstract
Penelitian ini dengan judul Pertimbangan Hakim Dalam Menjatuhan Hukuman Pidana BagiAnggota Tentara Nasional Indonesia Yang Melakukan Tindak Pidana Desersi,penelitian ini dilakukandi Wilayah Hukum Pengadilan Militer III-19 Jayapura, metode dalam penelitian ini adalah yuridisnormatif dan yuridis empirik, Adapun kesimpulan dari penelitian ini adalah Pertimbangan hakimdalam menjatuhkan pidana terhadap anggota TNI telah sesuai mengacu pada Pasal 86 sampaidengan Pasal 89 KUHPM terdapat ketidak sesauaian tentang Sanksi pidana desersi. Hal ini terbuktidengan dakwaan yang diberikan oleh oditur militer sehingga berdampak pada sangsi yang diberikanhakim, Faktor penjatuhan hukuman dalam proses tindak pidana desersi terdapat faktor internal danexternal yang mana berdasarkan hasil penelitian terdapat adanya faktor di luar lingkungan sehinggaberdapak pada penerapan Hukum pidana desersi
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 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".