Membangun Langkah Promotif-Preventif Terkait Stunting Melalui Pemanfaatan Hasil Pertanian Jewawut (Setaria italica) di Desa Lambanan, Kabupaten Polewali Mandar
Bibliographic record
Abstract
Tingkat kasus stunting yang tinggi di Provinsi Sulawesi Barat perlu diatasi. Maka, upaya penanggulangan bersifat urgen untuk menekan peningkatan prevalensinya. Langkah promotif-preventif yang dapat dilakukan adalah mengedukasi masyarakat dan memanfaatkan hasil pertanian lokal. Bahan pangan lokal dapat dimaksimalkan fungsinya untuk perbaikan gizi anak stunting jika diolah dengan baik. Desa Lambanan, di Kecamatan Balanipa, Kabupaten Polewali Mandar, Provinsi Sulawesi Barat salah satu desa yang memiliki potensi sumber pangan yang beragam seperti tersedianya pangan lokal Jewawut (Setaria italica). Meskipun Jewawut merupakan komoditi pertanian utama masyarakat Lambanan namun belum diolah secara maksimal untuk menanganai persoalan gizi anak-anak. Maka kegiatan pengabdian ini fokus menyebarluaskan pengetahuan tentang potensi jewawut yang dapat digunakan untuk pencegahan stunting. Selain itu kami melakukan pelatihan tentang cara mengolah Jewawut menjadi bubur MPASI yang kaya gizi dan protein. Hasil pengabdian ini menunjukkan ada peningkatan pengetahuan partisipan tentang jewawut dan tunting. Sebelum kegiatan pengetahuan partisipan yang terdiri dari 35 orang berada di angka 75,4 dan setelah penyuluhan dan praktik naik menjadi 84,29.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.013 | 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".