ANALISIS EFEKTIVITAS PENGELOLAAN AIR LIMBAH RUMAH SAKIT BHAYANGKARA KUPANG
Bibliographic record
Abstract
Hospitals are significant producers of liquid waste that have the potential to pollute the environment if not properly managed. Hospital wastewater contains organic and inorganic substances, pathogenic microorganisms, and hazardous chemicals. This study aims to evaluate the effectiveness of the Wastewater Treatment Plant (WWTP) at Bhayangkara Hospital Kupang based on chemical and microbiological parameters, including pH, temperature, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), oil and grease, and total coliform. The study uses a descriptive qualitative method with secondary data analysis from laboratory results. The results show that all parameters are below the threshold of environmental quality standards set by the Ministry of Environment Regulation No. 5 of 2014, with values for: pH (7.255), temperature (28°C), BOD (38.7 mg/L), COD (76 mg/L), TSS (0.06 mg/L), TDS (363 mg/L), oil and grease (0.016 mg/L), and total coliform (438/100 mL). These results indicate that the WWTP at Bhayangkara Hospital Kupang operates effectively in treating wastewater, making the discharged wastewater suitable for disposal into the environment and in compliance with the established quality standards.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.018 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".