FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN KEJADIAN ANEMIA PADA IBU HAMIL DI WILAYAH KERJA PUSKESMAS CIPUTAT TAHUN 2019
Bibliographic record
Abstract
Abstract Backgrounds: According to the Banten Provincial Health Office in 2019, one of the biggest contributors to the maternal mortality rate was bleeding during childbirth, around 37%. The high maternal mortality rate in Banten province can reach up to 135 cases of maternal death per 100,000 live births. Based on the prevalence of anemia in pregnant women in 2019 in the Ciputat Health Center Work Area, which was 44.4%. The object of this study: To find out the description of the factors related to the incidence of anemia in pregnant women in the work area of the Ciputat Health Center in 2019. Methods: Desain studi cross-sectional dengan data sekunder Formulir laporan ibu hamil risiko tinggi tahun 2019 di Puskesmas Ciputat. Sampel sebanyak 163 orang, pengambilan dilakukan dengan teknik total random sampling. Analisis data menggunakan uji chi square (α = 0,05). Result : The variable associated with the incidence of anemia in pregnant women is nutritional status (p. value = 0.000, OR = 5.27). Variables that are not related are parity (p. value = 0.444, OR = 0.69), maternal age (p. value = 0.673, OR = 0.81), abortion (p. value = 1,000, OR = 0.988), age pregnancy (p value = 0.837, OR = 1.19). Conclusion : The incidence of anemia in pregnant women in the Ciputat Health Center Work Area in 2019 the majority experienced anemia as many as 149 people (82.2%). Based on the results of the analysis of correlation signiantara relationship Nutritional Status with the incidence of anemia in pregnant women in the Puskesmas Ciputat 2019 with p value = 0.000 and OR = 5.27 value. Keywords: Anemia, Pregnant woman Abstrak Latar belakang: Menurut Dinas Kesehatan Provinsi Banten tahun 2019 salah satu penyumbang AKI terbesar adalah perdarahan saat melahirkan sekitar 37%. tingginya kasus angka kematian ibu di provinsi Banten dapat mencapai hingga 135 kasus kematian ibu per 100.000 angka kelahiran hidup. Berdasarkan prevalensia anemia ibu hamil pada tahun 2019 di Wilayah Kerja Puskesmas Ciputat yaitu sebesar 44,4% Tujuan penelitian: Untuk mengetahuinya gambaran faktor-faktor yang berhubungan dengan anemia pada ibu hamil di wilayah kerja Puskesmas Ciputat tahun 2019. Metode: Desain studi cross-sectional dengan data sekunder form laporan ibu hamil resiko tinggi. Sampel sebanyak 180 orang, pengambilan dilakukan dengan teknik total random sampling. Analisis data menggunakan uji chi square (α = 0,05). Hasil: Variabel yang berhubungan dengan kejadian anemia pada ibu hamil yaitu status gizi (p. value= 0,000, OR = 5,27). Variabel yang tidak behubungan yaitu paritas (p. value= 0,444, OR = 0,69), usia ibu (p. value= 0,673, OR = 0,81), usia kehamilan (p. value= 0,837, OR = 1,19) Kesimpulan: Kejadian Anemia pada ibu hamil di Wilayah Kerja Puskesmas Ciputat tahun 2019 mayoritas mengalami Anemia sebanyak 149 orang (82.2%). Berdasarkan hasil analisis hubungan terdapat hubungan yang signifikan antara Status Gizi dengan kejadian Anemia pada ibu hamil di Wilayah Kerja Puskesmas Ciputat tahun 2019 dengan p value = 0,000 dan nilai OR = 5,27. Kata Kunci: Anemia, Ibu hamil.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.019 | 0.002 |
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".