Hubungan Pengetahuan Dengan Kepatuhan Ibu Hamil Dalam Mengkonsumsi Tablet Zat Besi (Fe) Di Wilayah Kerja Puskesmas Lawanga Kabupaten Poso
Bibliographic record
Abstract
Latar Belakang: Tablet zat besi (Fe) sebagai suplemen yang diberikan pada ibu hamil menurut aturan harus dikonsumsi setiap hari, namun karena berbagai alasan misalnya pengetahuan, sikap dan tindakan ibu hamil yang kurang baik, efek samping tablet yang ditimbulkan tablet tersebut dapat menyebabkan seseorang untuk kurang mematuhi konsumsi tablet zat besi (Fe) secara benar sehingga tujuan dari pemberian tablet tersebut tidak tercapai. Tujuan: Mengetahui Hubungan Pengetahuan Dengan Kepatuhan Ibu Hamil Dalam Mengkonsumsi Tablet Zat Besi (Ferossus) Di Wilayah Kerja Puskesmas Lawanga Kabupaten Poso. Metode Penelitian: Jenis penelitian yang digunakan adalah deskriptif analitik dengan pendekatan cross sectional. Jumlah responden sebanyak 46 ibu hamil dengan menggunakan tehknik total Sampling. Data dianalisa dengan menggunakan uji Chi-square. Hasil penelitian : Menunjukkan bahwa 56,5 % responden memiliki pengetahuan baik, tentang tablet zat bezi (Fe), Sebesar 60,9% responden patuh mengkonsumsi tablet zat besi (Fe). Ada hubungan Pengetahuan dengan Kepatuhan Ibu Hamil dalam Mengkonsumsi Tablet Zat Besi (Fe) nilai p = 0,000 (p<0,05) Kesimpulan: Ada hubungan antara Pengetahuan dengan Kepatuhan Ibu Hamil dalam Mengkonsumsi Tablet Zat Besi (Fe) di Puskesmas Lawanga Kabupaten Poso.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".