Analisis Kualitas Air Isi Ulang Usaha Air Rebusan (UAR) Berdasarkan Standar Kesehatan di Kabupaten Merangin
Bibliographic record
Abstract
Enthusiasts for the refill drinkig water the Boiled Water Business (UAR) in several districts in Jambi Province are increasing. The quality of the water used is not guaranteed when compared to the Refill Drinking Water Depot (DAMIU) because there has never been a quality check and the form of supervision has not been officially legalized. The aim of the study was to analyze factors related to the quality of refilled water from UAR. The research method is mixed method. Primary data was collected in field and Labkesda Merangin district, secondary data from the Merangin District Health Office, the Central Statistics Agency, and Puskesmas in the Merangin District from April to August 2022. The population is the UAR depot in Merangin District totaling 38 samples. Interviews with questionnaires and field observations. The dependent variable is the physical and bacteriological quality of UAR refilled water, the independent variable is the aspect of the place, the aspect of the equipment, the source of raw water, the hygiene of the handlers and the guidance. Univariate and bivariate analysis using chi-square test, at 95% confidence level. The results of the study found aspects that did not meet the requirements for physical worthiness included: place (42.1%), handler hygiene (44.7%), equipment (36.8%), raw water (36.8%) and there were 55.3 % Undeveloped UAR. There is a relationship between aspects of equipment, raw water, handler hygiene and coaching with recycled water quality. It has not been proven that there is a relationship between the aspect of the place and the quality of the return water. The reason consumers choose UAR refilled water is because of the belief in water quality assurance and the hygiene of the handler. Boiled water business was chosen by UAR entrepreneurs because of the small capital, the amount of profit, high consumer demand and the ease of processing. It is hoped that in the future all parties in Merangin district, especially the government, can pay attention to this effort so that its quality is guaranteed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".