ANALISIS PENGETAHUAN LANSIA TERHADAP PEMENUHAN PERSONAL HYGIENE DI PUSKESMAS WERDHI AGUNG
Bibliographic record
Abstract
According to WHO, the highest status of elderly is in mainland ASIA, the number predicted to be the highest in the world, which is 400 million people or ½ of the world's elderly. Indonesia is one of the ASIA regions where the number of elderly people has increased by 0.89%. A large number of elderly people in Indonesia is one of the impacts of increasing the life expectancy of the Indonesian people. This research is a quantitative type with a descriptive approach using cross-sectional methods. Held in June-July 2020 at the Werdhi Agung Puskesmas, with a population of 158 elderly people, and a sample of 32 with purposive sampling method. This research was conducted to determine the relationship between the level of knowledge of the elderly with personal hygiene. The results showed that there was a significant relationship between the knowledge of the elderly and the personal hygiene behavior performed by the elderly. The low knowledge of the elderly about personal hygiene behavior in the working area of ??Werdhi Agung Community Health Center is the main cause of the elderly who do not have sufficient health and welfare status. Knowledge is one of the main factors of several factors that can change and motivate health behavior, while knowledge is influenced by age and education.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".