PEMBANGUNAN WILAYAH PESISIR DAN LAUTAN DALAM PERSPEKTIF NEGARA KEPULAUAN REPUBLIK INDONESIA
Bibliographic record
Abstract
PEMBANGUNAN WILAYAH PESISIR DAN LAUTAN DALAM PERSPEKTIF NEGARA KEPULAUAN REPUBLIK INDONESIA Regional Development in Coastal and Ocean in Archipelago Perspective of The Republic of Indonesia Ridwan Lasabuda1 ABSTRACT Indonesian as an archipelagic state has been recognized internationally (UNCLOS 1982), later ratified by Act 17 of 1985. Under UNCLOS 1982, the total maritime area of Indonesia is 5.9 million km2, consisting of 3.2 million km2 of territorial waters and 2.7 km2 of Economic Exclusive Zone (Zone Ekonomi Ekslusif), not including the continental shelf. This makes Indonesia as the largest archipelagic state in the world. However, the development of marine and fisheries for this is still far from expectations, while large potential of natural resources and environmental services are relatively unexploited in coastal areas, small islands and ocean in Indonesian archipelago. Keywords : coastal and ocean, development, Indonesian, archipelago ABSTRAK Sebagai negara kepulauan, Indonesia telah diakui dunia secara internasional (UNCLOS 1982) yang kemudian diratifikasi oleh Indonesia dengan Undang-Undang No.17 Tahun 1985. Berdasarkan UNCLOS 1982, total luas wilayah laut Indonesia seluas 5,9 juta km2, terdiri atas 3,2 juta km2 perairan teritorial dan 2,7 km2 perairan Zona Ekonomi Eksklusif, luas tersebut belum termasuk landas kontinen. Hal ini menjadikan Indonesia sebagai negara kepulauan terbesar di dunia. Namun demikian, pembangunan bidang kelautan dan perikanan hingga saat ini masih jauh dari harapan. Padahal wilayah pesisir dan pulau-pulau kecil dan lautan kepulauan Indonesia disimpan potensi sumber daya alam dan jasa lingkungan yang sangat besar dan belum dimanfaatkan secara optimal. Kata kunci : pesisir dan laut, pembangunan, Indonesia, kepulauan 1 Laboratorium Pengelolaan Wilayah Pesisir Terpadu, FPIK UNSRAT
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".