UJI DAYA HAMBAT AMOKSISILIN DAN KOTRIMOKSAZOL TERHADAP ISOLAT ESCHERICHIA COLI PADA SUMBER AIR BAKU SUNGAI CITARUM
Bibliographic record
Abstract
Sungai Citarum merupakan sungai terpanjang di wilayah Provinsi Jawa Barat. Aliran sungai ini di daerah Kabupaten Karawang memiliki banyak manfaat bagi kehidupan manusia, salah satunya sebagai sumber air baku untuk layanan air bersih. Sungai Citarum telah dilaporkan mengalami pencemaran sehinggga mengindikasikan keberadaan bakteri patogen E. coli. Bakteri ini mampu menyebabkan infeksi pada manusia seperti infeksi saluran pencernaan (diare) dan infeksi saluran kemih (ISK). Penggunaan antibiotik menjadi salah satu solusi untuk mengobati infeksi akibat bakteri pada manusia, namun antibiotik seringkali mengalami resistensi. Hal ini berbahaya bagi kehidupan manusia karena dapat mengakibatkan terapi menjadi tidak efektif, meningkatkan morbiditas dan mortalitas. Sensitivitas suatu antibiotik berpengaruh terhadap keberhasilan pengobatan, maka penelitian ini bertujuan untuk menguji daya hambat antibiotik amoksisilin dan kotrimoksazol.yang digunakan untuk mengobati infeksi akibat bakteri E. coli. Penelitian ini adalah penelitian eksperimental yang meliputi uji pendugaan, uji penegasan, pewarnaan gram, dan uji daya hambat antibiotik terhadap bakteri dengan metode difusi cakram. Berdasarkan hasil penelitian, amoksisilin dan kotrimoksazol masih bersifat sensitif terhadap isolat E. coli. Uji daya hambat yang dilakukan pada amoksisilin menunjukkan diameter zona hambat ≥17 mm sedangkan pada kotrimoksazol menunjukkan diameter zona hambat ≥16 mm.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".