HUBUNGAN PENGETAHUAN DAN MOTIVASI IBU DENGAN PEMBERIAN MP-ASI DI WILAYAH KERJA PUSKESMAS RAWASARI KOTA JAMBI
Bibliographic record
Abstract
Prevalence of malnutrition in Indonesia 2013, consists of 5.7% and 13.9% malnutrition. Giving breast milk too early may have a negative impact on the health of the baby. In infants who have missed the MP-ASI will lead to malnutrition. This research was conducted using the analytical method. The research was conducted in 2-14 September 2016. The population in this study were mothers of infants aged 6-11 months in Puskesmas Rawasari Jambi City in Agust 2016 that is 73 babies. The research sample is taken by simple random sampling technique totaling 42 babies. Collecting data in this study using a questionnaire measuring instrument with a questionnaire. The analysis used were univariate and bivariate. The results showed that most respondents had a good knowledge of 30 respondents (71%), less well motivated as many as 25 respondents (40%) and have good behavior, namely 23 respondents (55%). The analysis showed that there is not a relationship between the mother's knowledge with the mother’s habit of giving breast milk p value 0,192.and motivationshowed that there is a relationship with the mother's habit of giving breast milk p value 0,008 in that region Rawasari Work Puskesmas Kota Jambi.And alpha value 0.005.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".