Berat Badan Lahir, Panjang Badan Lahir, dan Jenis Kelamin Sebagai Faktor Kejadian Stunting di Provinsi Banten
Bibliographic record
Abstract
Stunting masih menjadi masalah kesehatan masyarakat utama di Indonesia meskipun prevalensinya menunjukkan penurunan secara bertahap. Penelitian ini bertujuan untuk menganalisis hubungan antara berat badan lahir, panjang badan lahir, dan jenis kelamin bayi dengan kejadian stunting pada balita di Provinsi Banten. Penelitian deskriptif kuantitatif ini menggunakan data sekunder Survei Status Gizi Indonesia (SSGI) tahun 2021 dengan jumlah sampel sebanyak 3.671 balita. Berat badan lahir diklasifikasikan menjadi berat badan lahir rendah dan normal, sedangkan panjang badan lahir dibedakan menjadi <48 cm dan ≥48 cm. Analisis data dilakukan menggunakan uji chi-square. Hasil penelitian menunjukkan bahwa berat badan lahir rendah berhubungan signifikan dengan kejadian stunting (p=0,001; OR=2,473). Balita dengan panjang badan lahir <48 cm memiliki risiko lebih tinggi mengalami stunting (p=0,001; OR=2,413). Selain itu, balita laki-laki lebih berisiko mengalami stunting dibandingkan perempuan (p=0,007; OR=1,238). Temuan ini menegaskan pentingnya peningkatan intervensi kesehatan ibu dan anak sejak masa kehamilan dan awal kehidupan untuk mencegah stunting.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".