OPTIMASI TEMPERATUR DAN KONSENTRASI NaOH PADA PEMBUATAN KARBOL DARI MINYAK JELANTAH
Bibliographic record
Abstract
Karbol adalah cairan pembersih non-detergenik (tidak mengandung deterjen) dan desinfektan yang memiliki wangi tertentu. Pada proses pembuatan karbol dari minyak jelantah, digunakan metode pemanasan untuk pembuatannya. Adapun tahapan penelitian ini dimulai dari preparasi bahan pembuatan, penjernihan awal bahan pembuatan, analisa warna, analisa koefisien fenol, analisa pH, dan analisa stabilitas pada air sadah. Berdasarkan hasil analisa yang paling optimum didapat pada karbol minyak jelantah dengan pemasakan di temperatur 90 °C. Pada konsentrasi NaOH 10 % nilai yang didapat pH = 7, koefisien fenol = 2,22, warna = coklat, stabilitas emulsi pada air sadah = stabil. Pada konsentrasi NaOH 20 % nilai yang didapat pH = 9, koefisien fenol = 2,22, warna = coklat, stabilitas emulsi pada air sadah = stabil. Pada konsentrasi NaOH 30 % nilai yang didapat pH = 10, koefisien fenol = 2,77, warna = coklat, stabilitas emulsi pada air sadah = stabil. Pada konsentrasi NaOH 40 % nilai yang didapat pH = 11, koefisien fenol = 2,77, warna = coklat, stabilitas emulsi pada air sadah = stabil. Hasil yang diperoleh sesuai dengan BSN (SNI-06-1842-1995).
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".