Perilaku Ibu Hamil Dalam Pelaksanaan P4K Berhubungan Dengan Kesiapan Ibu Hamil Menghadapi Komplikasi
Bibliographic record
Abstract
Salah satu upaya untuk mencegah keterlambatan penanganan komplikasi adalah dengan adanya program P4K. Apabila setiap ibu hamil melaksanakan P4K diharapkan bila terjadi komplikasi pada kehamilannya akan dapat tertangani sedini mungkin. Tujuan dari penelitian ini adalah untuk menganalisis hubungan perilaku ibu hamil dalam pelaksanaan P4K dengan kesiapan ibu hamil menghadapi komplikasi di Desa Kedok Wilayah Kerja Puskesmas Turen. Penelitian ini menggunakan desain studi korelasional dengan pendekatan cross sectional, populasi sebanyak 45 orangibu hamil, dan sampling menggunakan teknik simple random sampling dengan jumlah sampel sebanyak 40 orang ibu hamil yang telah memenuhi kriteria inklusiyaitu ibu hamil yang sudah mendapatkan penjelasan tentang P4K dan telah memiliki stiker P4K, bersedia menjadi responden. Instrumen penelitian menggunakan kuisioner perilaku ibu hamil dalam pelaksanaan P4K dan kuisioner kesiapan ibu hamil meghadapi komplikasi. Analisa data menggunakan ujichi squaredengan tingkat signifikansi α 0,05.Hasil penelitian menunjukkan adanyahubungan antara perilaku ibu hamil dalam pelaksanaan P4K dengan kesiapan ibu hamil menghadapikomplikasi (p-value <0,001). Ibu hamil dapatmelaksanakan P4K sebagai upaya untuk meningkatkan kesiapan ibu hamil dalam menghadapi kemungkinan terjadinya komplikasi.
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".