Inovasi Pelaksanaan Posyandu Selama Masa Pandemi Covid-19: Studi Kualitatif di Wilayah Kerja Puskesmas Campalagian
Bibliographic record
Abstract
Posyandu cadres play an important role in assisting Public Health Center in carrying out the functions of implementing health efforts and have a strategic position to prevent stunting problems, especially in time the Covid-19 pandemic. This study aimed to describe the implementation of Integrated Health Post (Posyandu) in the working area of the Campalagian Health Center during the Covid-19 pandemic in 2020. This study qualitative used a phenomenology approach which was carried out in the working area of the Campalagian Health Center in July - September 2020. A total of 10 Posyandu cadres were the main informants. Data were collected through in-depth interviews for 60 – 90 minutes conducted at the homes of Posyandu cadres while still paying attention to health protocols. Cadres did not carry out Posyandu in April and May 2020 following local government regulations or in certain months when there was an increase in cases of Covid-19 in the area. In implementing the Posyandu during the pandemic, cadres made several innovations such as setting up emergency handwashing facilities, arranging visit schedules, and the distance of waiting chairs at the Posyandu, requiring them to bring their own sharoong from home for weighing toddlers and disinfecting the Posyandu room. In conclusion, cadres make innovations in the implementation of Posyandu during the pandemic such as preparing emergency hand washing facilities, arranging visit schedules and waiting chair spacing at Posyandu, requiring them to bring their own gloves and disinfecting the Posyandu room. The implementation of Posyandu during the Covid-19 pandemic can prevent an increase in nutritional problems in mothers and stunting problems in toddlers. Therefore, the local government is expected to support the implementation of Posyandu routinely such as ensuring the availability of PPE for posyandu cadres, mothers and toddlers. So that Posyandu can still be implemented while still observing health protocols.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".