Efektivitas Pelaksanaan Asas Peradilan Sederhana, Cepat Dan Biaya Ringan Berkaitan Dengan Yurisdiksi Pengadilan Negeri Sigli
Bibliographic record
Abstract
Asas peradilan sederhana, cepat dan biaya ringan telah diatur dalam UU, Hakim wajib menerapkan asas tersebut dengan tujuan memberikan keadilan dan menghematkan waktu bagi para pihak yang menyelesaikan perkara. Begitu juga hakim yang memeriksan dan menutuskan perkara di Pengadilan Negeri Sigli, meskipun PN Sigli memiliki 2 wilayah yurisdiksi yaitu Pidie dan Pidie Jaya. Tujuan penulisan untuk mengetahui efektifitas dan hambatan dalam pelaksanaan asas peradilan sederhana, cepat dan biaya ringan di PN Sigli. Metode yang digunakan adalah metode penelitian yuridis empiris. Hasil penelitian menunjukkan: pertama. Penerapan asas pengadilan sederhana, cepat dan biaya ringan belum berjalan dengan efektif dan sempurna di PN Sigli. Kedua. Pelaksanaan asas sederhana, cepat dan biaya ringan di PN Sigli masih mendapat berbagai macam hambatan, yaitu: Pemanggilan Tidak Ketemu Para Pihak di Tempat, Keuchik Lupa Menginformasikan kepada Pihak, Lupa Mencamtukan Materai Pada Seluruh Bukti, Banyaknya Perkara yang Masuk, Banyaknya Saksi yang Dihadirkan, para pihak Tidak Serius, dan gagalnya proses mediasi.The principle of simple, fast and low-cost justice has been regulated in the Law, the Judge is obliged to apply the principle with the aim of providing justice and saving time for the parties who settle the case. Likewise the judge who examined and decided on the case in the Sigli District Court, even though the Sigli District Court had 2 jurisdictions namely Pidie and Pidie Jaya. The purpose of writing is to find out the effectiveness and obstacles in the implementation of simple, fast and low-cost judicial principles in Sigli District Court. The method used is an empirical juridical research method. The results of the study show: first. The application of a simple, fast and low cost court principle has not been effective and perfect in Sigli District Court. Second. The implementation of simple, fast and low-cost principles in Sigli District Court still gets various obstacles, namely: Summoning Not Meeting Parties at the Place, Keuchik Forgot to Inform the Parties, Forgot to Stamp on All Evidence, Number of Cases Entered, Number of Witnesses Presented, the parties are not serious, and the mediation process fails.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".