ANALISIS YURIDIS PENANGKAPAN IKAN TANPA SIPI PADA WILAYAH PULAU BAWEAN BERDASARKAN UU NOMOR 45/2009 TENTANG PERUBAHAN ATAS UU NOMOR 31/2004 TENTANG PERIKANAN (STUDI PUTUSAN PENGADILAN NEGERI BATANG NOMOR: 23/PID.SUS/2014.PN.BTG)
Bibliographic record
Abstract
Kegiatan penangkapan ikan tanpa memiliki SIPI merupakan kegiatan yang tidak dibenarkan untuk dilakukan. Meskipun ada peraturan UU yang mengatur mengenai larangan tersebut, masih ada pihak tertentu yang melanggar peraturan tersebut. Pokok permasalahan yang dibahas dalam skripsi ini adalah 1)Apakah penangkapan ikan tanpa Surat Izin Penangkapan Ikan (SIPI) yang dilakukan oleh KMN.BINTANG SAMUDRA II melanggar UU Nomor 45/2009 Tentang Perubahan Atas UU Nomor 31/2004 dan Perda Provinsi Jatim Nomor 4/2005 serta Perda Kabupaten Gresik Nomor 8/2007, 2)Apakah penangkapan ikan tanpa Surat Izin Penangkapan Ikan (SIPI) yang dilakukan oleh KMN.BINTANG SAMUDRA II melanggar UU Nomor 45/2009 Tentang Perubahan Atas UU Nomor 31/ 2004 dan Perda Provinsi Jatim Nomor 4/2005 serta Perda Kabupaten Gresik Nomor 8/2007. Untuk menjawab permasalahan tersebut dilakukan penelitian hukum normatif dengan sifat deskriptif analisis, data yang digunakan data sekunder, pengolahan data kualitatif, dan penarikan kesimpulan menggunakan logika deduktif. Hasil penelitian menunjukan ada dua Perda yang mengatur hal tersebut, yaitu Perda Kabupaten Gresik Nomor 8/2007 Tentang Perjanjian Usaha Perikanan dan Perda Provinsi Jatim Nomor 4/2005 Tentang Usaha Perikanan dan Usaha Kelautan Provinsi Jatim, Pertimbangan Hakim dalam Putusan PN Batang Nomor: 23/Pid.Sus/2014/PN.BTG berkesimpulan bahwa Yaspaun terbukti bersalah melakukan tindak pidana penangkapan ikan tanpa Surat Izin Penangkapan Ikan (SIPI).
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".