WAWASAN IBU MENYUSUI TENTANG STUNTING DI WILAYAH KERJA UPT PUSKESMAS PENGALIHAN KECAMATAN ENOK KABUPATEN INDRAGIRI HILIR
Bibliographic record
Abstract
Stunting dapat diartikan suatu kondisi gagal tumbuh pada anak balita akibat dari kekurangan gizi kronis sehingga anak menjadi terlalu pendek untuk usianya. Tidak terlaksananya inisiasi menyusu dini (IMD), gagalnya pemberian air susu ibu (ASI) eksklusif, dan proses penyapihan dini dapat menjadi salah satu faktor terjadinya stunting. Tujuan dari penelitian ini adalah untuk mengetahui wawasan ibu menyusui tentang stunting di wilayah kerja UPT Puskesmas Pengalihan Kecamatan Enok Kabupaten Indragiri Hilir. Jenis penelitian ini bersifat deskriptif. Populasi dalam penelitian ini adalah seluruh ibu menyusui diwilayah kerja UPT Puskesmas Pengalihan Enok sebanyak 102 orang. Sampel yang digunakan sebanyak 81 Ibu menyusui. Tehnik pengambilan samapel adalah dengan random sampel. Instrumen penelitian menggunakan kuesioner. Data yang didapat diolah secara manual dan disajikan dalam bentuk table. Hasil penelitian diperoleh 41 responden (50,62%) memiliki wawasan kurang tentang stunting. Maka disimpulkan wawasan ibu menyusui di wilayah kerja UPT puskesmas penglihan enok kurang. Disarankan kepada masyarakat khususnya ibu menyusui hendaknya rajin mencari informasi baik dari media elektronik maupun dengan ikut kegiatan-kegiatan penyuluhan kesehatan.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".