PENGARUH PEMBERIAN BUBUR INSTAN MORPHALUS (TEPUNG DAUN KELOR, TEPUNG KACANG MERAH, TEPUNG IKAN GABUS) TERHADAP PENINGKATAN BERAT BADAN BAYI GIZI KURANG USIA 6-11 BULAN DI PUSKESMAS TAMAN BACAAN PALEMBANG
Bibliographic record
Abstract
Background: Undernutrition is still a major nutritional problem in Indonesia. Babies are one of the vulnerable groups experiencing nutritional problems. The direct cause of the occurrence of malnutrition is one of which is influenced by the intake of nutrients. Low energy, protein and fat intake causes optimal utilization of nutrients and susceptible to infectious diseases (Diniyyah, 2017). Therefore, with the provision of morphalus instant porridge that is high in energy and protein can help increase weight. Method: This research is a quasi-eskperimen study with a pre-test research design and post test with control group design. The study was conducted from January-March 2022. The sample number of 20 treatment respondents and 20 comparison respondents were carried out by purposive sampling. Results: Based on statistical tests in the treatment group and comparison group obtained the value of the baby's weight before and after the intervention with a p-value (<0.05) Conclusion: Morphalus instant porridge has an effect on increasing the weight of malnourished infants aged 6-11 months in the Working Area of the Taman Bacaan Palembang Health Center Keywords: Undernutrition, Complementary food
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".