Hubungan antara Pengetahuan, Dukungan Keluarga dan Personal Hygiene dengan Perawatan Luka Perineum Masa Nifas di Wilayah Kerja Puskesmas Belida Darat Kecamatan Darat Kabupaten Muara Enim Tahun 2021
Bibliographic record
Abstract
Perineal care is an effort to provide fulfillment of the need for comfort by nourishing the area between the two thighs which is limited between the anal canal and the external genitalia in women who have given birth to avoid infection. The prevalence of childbirth mothers who experience perineal rupture in Indonesia in the age group of 25-30 years is 24% and at the age of 32-39 years is 62%. In 2013 57% of mothers received perineal sutures (28% due to episiotomy and 29% due to spontaneous tears). To determine the relationship between knowledge, family support and personal hygiene with postpartum perineal wound care in The Working Area of the Belida Darat Health Center, Belida Darat District, Muara Enim Regency. This research is an analytical survey quantitative research with a cross sectional approach, namely research with observations in a period and research subjects are observed once during the study. The results of the chi-square statistical test of the knowledge variable obtained value = 0.002, personal hygiene variable obtained value = 0.023, and the family support variable obtained value = 0.025 this indicates there is a significant relationship between family support and perineal wound care in the Region Belida Darat Health Center in Belida Darat K . District Muara Enim Regency in 2021.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".