REMOVAL COD DAN TSS LIMBAH CAIR RUMAH POTONG AYAM MENGGUNAKAN SISTEM BIOFILTER ANAEROB
Bibliographic record
Abstract
Tingginya kandungan zat organik pada limbah cair industri rumah potong ayam (RPA) menyebabkan limbah cair tersebut tidak boleh dibuang langsung ke lingkungan akuatik. Peningkatan kebutuhan protein dari sumber konsumsi daging ayam, menyebabkan peningkatan limbah cair industri RPA. Oleh karena itu diperlukan suatu alternatif penyelesaian untuk menurunkan kandungan beban pencemar pada limbah cair industri RPA agar kualitas effluent yang dihasilkan tidak mencemari lingkungan serta memenuhi baku mutu yang telah ditetapkan. Pada penelitian ini pengolahan limbah cair RPA dilakukan dengan menggunakan sistem biofilter anaerob media bioball, dengan variasi waktu tinggal dan konsentrasi influnt. Sampel pengukuran konsentrasi Chemical Oxygen Demand (COD) influent berturut turut sebesar 734 mg/L, 388 mg/L, dan 248 mg/L. Konsentrasi Total Suspended Solid (TSS) dalam air baku limbah RPA sebesar 88 mg/L, 70 mg/L, dan 54 mg/L. Setelah dilakukan pengolahan mengalami penurunan konsentrasi COD dan TSS terhadap semua variasi konsentrasi. Waktu tinggal yang paling efektif dalam menurunkan kadar COD dan TSS pada limbah cair RPA adalah 7 jam.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".