Ternak Kambing Sebagai Sumber Pendapatan Saat Kelapa Sawit Replanting Menuju Kemandirian Pangan
Bibliographic record
Abstract
Provinsi Riau saat ini banyak perkebunan kelapa sawit yang seharusnya sudah melakukan peremajaan (Replanting) ,tetapi banyak masyarakat yang tidak mau melakukannya karena tidak punya pendapatan atau berkurang pendapatannya sampai kelapa sawit dapat berproduksi, salah satu yang dapat menjadi sumber pendapatan bagi keluarga petani adalah dengan melakukan usaha ternak kambing. Penelitian ini bertujuan untuk menemukan sumber pendapatan petani saat kelapa sawit replanting melalui usaha ternak kambing. Penelitian ini menggunakan metode survey, pengambilan sampel secara purposive sampling, yang dijadikan sampel adalah petani yang memelihara kambing saat kelapa sawit replanting . data diperoleh menghitung pandapatan usaha ternak kambing . Data primer diperoleh langsung dari petani dan data sekunder diperoleh dari instansi dan dinas terkait dengan penelitian ini. Analisa dilakukan dengan menghitung sumber pendapatan petani, .Hasil penelitian ini menunjukan pendapatan petani dari memelihara ternak kambing saat kelapa sawit replanting RP 983.00 perbulan. dengan RCR 1,24.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".