PENGARUH EKSTRAK DAUN KELOR TERHADAP STATUS GIZI BALITA DI DESA TEJAKULA
Bibliographic record
Abstract
Latar Belakang: Stunting (tinggi/panjang berdasarkan usia dengan z-score kurang dari -2 SD) dan defisiensi mikronutrien adalah dua contoh masalah gizi. Hal tersebut menjadikan status gizi balita sebagai indikator kesehatan yang penting karena balita merupakan kelompok yang rentan terhadap masalah gizi. Daun kelor mengandung arginin dan histidin, yang sangat penting bagi anak-anak yang tidak dapat menghasilkan cukup protein untuk pertumbuhan mereka. Penelitian ini bertujuan untuk mengetahui pengaruh pemberian ekstrak daun kelor terhadap peningkatan status gizi balita. Metode: Jenis desain penelitian ini menggunakan metode penelitian eksperimental, analitis dengan desain kuasi-eksperimental. Desain yang digunakan adalah desain one-group pre-test dan post-test. Populasi dalam penelitian ini adalah semua anak usia 1 sampai 5 tahun yang mengalami kekurangan gizi berjumlah sepuluh anak dengan total sampling. Hasil: penelitian menunjukkan bahwa semua balita mengalami peningkatan berat dan tinggi badan setelah diberi 10 gram ekstrak daun kelor selama 14 hari. Hasil uji statistik Wilcoxon Signed Ranks Test, diperoleh nilai sig. = 0,002, yang berarti lebih kecil dari α 0,005, yang berarti pemberian ekstrak daun kelor berpengaruh signifikan terhadap status gizi balita.
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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 | 0.001 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".