INOVASI PEMANFAATAN LIMBAH KOTORAN SAPI SEBAGAI PUPUK ORGANIK (BOKASHI) DI DESA JUNGKE, KARANGANYAR
Bibliographic record
Abstract
Dusun Mandungan, Karanganyar sebagian besar masyarakatnya memiliki mata pencaharian sebagai peternak sapi yang hanya memaksimalkan hasil produktivitas sapi saja. Dibutuhkan inovasi agar limbah kotoran sapi dapat diolah secara tepat dan tentunya mampu menambahkan nilai ekonomi peternak. Tujuan dari penelitian ini yaitu untuk melakukan diversifikasi produk limbah kotoran sapi menjadi bahan baku pupuk organik. Metode yang digunakan dalam kegiatan penelitian ini yaitu deskriptif dan studi kasus sampel pupuk dengan waktu fermentasi yang berbeda yaitu sampel I selama 28 hari dan sampel II selama 21 hari. Hasil dari laboratorium uji kandungan terbaik yaitu pada pupuk organik sampel II dengan fermentasi selama 21 hari (C-Organik 32,04%; bahan organik 55,24%; N-total 1,82%; P2O5 total 1,22%; K2O total 1,08%; kadar air 18,22%; dan pH 6,81). Pembuatan Bank Bokashi ini sebagai gambaran kepada masyarakat untuk memanfaatkan limbah dan mengelola lingkungan sekitar lebih baik lagi dan menghasilkan nilai jual.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".