Hubungan Pengetahuan, Sikap dan Dukungan Keluarga Dengan Kepatuhan Ibu Hamil Trimester III Mengkonsumsi Tablet Besi (Fe) di Wilayah Kerja Puskesmas Karang Mukti Kecamatan Lalan Tahun 2021
Bibliographic record
Abstract
In Indonesia, there are 41 cases of anemia in pregnant women every day, and 20 women die due to anemia. This high number is due to the low ignorance of the mother about the dangers of anemia in pregnancy which tends to appear in the 1st and 3rd trimesters of pregnancy. Aims to determine the relationship between Knowledge, Attitude and Family Support with the Compliance of Pregnant Women in the Third Trimester Consuming Iron (Fe) Tablets in the Work Area of Karang Mukti Health Center, Lalan District. This type of research is an analytical survey using a cross sectional approach design. The population in this study were all mothers in the third trimester of 2021, which amounted to 186 people and the number of samples was 65 respondents. The sampling technique used was purposive sampling. Analysis of the data used is the chi-square statistical test with p value value (0.05). The results of this study from 65 respondents, there is a relationship between knowledge and adherence of pregnant women to consume Fe tablets, p value = 0.000, there is a relationship between attitudes and adherence to pregnant women taking Fe tablets, p value = 0.02 and there is a relationship between family support and compliance with pregnant women taking tablets. Fe p value = 0.03. It is expected to be able to improve health services to the community through various methods, both health counseling to reduce maternal mortality.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".