Profil Aktivitas Ekonomi Masyarakat Perikanan sekitar Waduk di Jawa Barat
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui profil kegiatan ekonomi masyarakat di sekitar waduk. Metode yang digunakan adalah Metode Deskriptif dengan pendekatan Kualitatif dan Kuantitatif. Pengambilan sampel menggunakan Tehnik Purposive Sampling, yaitu sampel dilakukan terhadap pelaku utama perikanan yang ada di 5 waduk (Waduk Jatiluhur, Waduk Cirata,Waduk Saguling,Waduk Jatigede, dan Waduk Darma). Tehnik pengumpulan data menggunakan wawancara dengan menggunakan instrumen berupa kuesioner yang berisi open dan close question. Dalam pengolahan data dilakukan penetapan nilai (skor) terhadap setiap pertanyaan yang berada dalam setiap sub sistem usaha. Hasil penelitian terhadap 5 waduk yang ditinjau dari 5 sub sistem usaha (sarana produksi, produksi, pasca produksi, pemasaran, dan layanan pendukung) diperoleh nilai (skor) sebagai berikut: Waduk Jatiluhur (10,96), Waduk Cirata (9,24), Waduk Saguling (10,86), Waduk Jatigede (9,32), dan Waduk Darma (8,92). Dari hasil penilaian tersebut, maka diperoleh gambaran tentang profil aktivitas ekonomi masyarakat di sekitar waduk. Semoga penelitian ini dapat dijadikan sebagai bahan referensi untuk menambah kepustakaan dan pengembangan pengetahuan tentang profil aktivitas ekonomi masyarakat di sekitar waduk.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".