Impact of Basic Sanitation and Healthy Behavior to Healthy Homes Condition in Cilegon City and Kutai Kartanegara District, Indonesia
Bibliographic record
Abstract
Healthy homes is a residential building that meets the health requirements as well as having healthy latrines, clean water facilities, solid waste disposal management, etc. The aim of this study was to determine the factors that most influence to healthy homes condition in Cilegon city and Kutai Kartanegara district in Indonesia. This study was done by using analytic survey methodology with cross sectional design. The Population in this study was householders in Cilegon city and Kutai Kartanegara district with total 800 and 1,200 respondents respectively. The result showed in Cilegon city and Kutai Kartanegara district respectively that healthy homes was 46.4% and 61.3%, 55.9 % and 57.3% having a good clean water resources, 82.3% and 71.9% having good excreta disposal facilities, 42.3% and 41.7 % doing good rubbish management, 56.1% and 36.6% having good drainage. The percentage of healthy behavior was 84.4% and 52.7%. Logistic regression analysis showed that waste management, drainage and personal hygiene were the most variables that influenced the healthy homes condition. As the conclusion, improving of the program and practices in basic sanitation facilities and personal hygiene is important to achieve national level of healthy community for Cilegon city and Kutai Kartanegara district.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".