HUBUNGAN DUKUNGAN SOSIAL DAN SIKAP IBU TERHADAP KEBERHASILAN PEMBERIAN ASI EKSKLUSIF DI WILAYAH PUSKESMAS BENAO KABUPATEN BARITO UTARA KALIMANTAN TENGAH
Bibliographic record
Abstract
Pendahuluan: Ibu menyusui di Indonesia masih banyak yang gagal melakukan pemberian ASI secara eksklusif. Penelitian ini bertujuan menganalisis hubungan dukungan sosial dan sikap ibu terhadap keberhasilan ASI Eksklusif. Metode: Desain penelitian ini menggunakan cross sectional. Sampel penelitian adalah 102 ibu menyusui yang dengan bayi berusia 6-23 bulan di wilayah Puskesmas Benao Kabupaten Barito Utara Kalimantan Tengah yang dipilih dengan teknik cluster sampling. Variabel dependen yaitu dukungan sosial dan sikap ibu, sedangkan variabel independen yaitu keberhasilan ASI eksklusif. Data dikumpulkan menggunakan dua kuesioner, kuesioner dukungan sosial di adaptasi dari Hughes Breastfeeding Support Scale dan kuesioner sikap menggunakan kuesioner dari Iowa Infant feeding Attitude Scale. Data kemudian dianalisis menggunakan Chi Square. Hasil: Hasil penelitian ini menunjukan tidak ada hubungan antara dukungan sosial dengan keberhasilan ASI eksklusif (p=0,270), ada hubungan antara sikap ibu dan keberhasilan ASI eksklusif (p=0,001). Diskusi: Dapat disimpulkan bahwa tidak ada hubungan dukungan sosial dengan keberhasilan pemberian ASI eksklusif. Sikap ibu sudah cukup baik dalam mendukung keberhasilan ASI eksklusif. Untuk membuat ASI eksklusif berhasil, perlu untuk memberdayakan orang-orang disekitar ibu dengan memberikan konseling dan informasi mengenai ASI eksklusif.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".