Upaya Peningkatan Produktivitas dan Keuntungan Hasil Tangkap dengan Mengubah Nelayan Buruh Menjadi Nelayan Pemilik
Bibliographic record
Abstract
Membangun dari daerah merupakan program utama dari pemerintahan Presiden Joko Widodo, maka program Ipteks Bagi Masyarakat (IbM) ini bertujuan untuk mendukung program pemerintah dengan meningkatkan produktivitas dan perekonomian nelayan tangkap di Dusun Duroa, Kota Tua, Provinsi Maluku dengan mengkonversi status mereka dari nelayan tangkap buruh menjadi nelayan pemilik dan memberikan modal, pelatihan, penyuluhan serta pendampingan. Program ini penting sebagai inisiasi untuk meningkatkan perekonomian nelayan tangkap Dusun Duroa yang sebagian besar nelayan tangkap yang berada di wilayah ini merupakan nelayan buruh. Hasil dari program ini sudah terlihat dampaknya dimana keuntungan nelayan tangkap meningkat sangat signifikan karena hasil yang didapatkan seluruhnya masuk ke nelayan tangkap dan produktivitasnya juga meningkat dengan teknik tangkap yang sesuai dengan perairan di sekitar wilayah desa Durua. Kata Kunci: IbM, Pengabdian, Nelayan Tangkap, Produktivitas.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".