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Record W4375951422 · doi:10.33024/jkm.v9i2.7499

The Relationship Of Mother Factors With Stunting Events At Puskesmas Muara Satu, Lhokseumawe City

2023· article· id· W4375951422 on OpenAlexaff
Nizan Nizan, Aida Fitriani, Rayana Iswani, Ernita Ernita, Elvieta Elvieta

Bibliographic record

VenueJKM (Jurnal Kebidanan Malahayati) · 2023
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineHumanitiesPediatricsEnvironmental healthArt

Abstract

fetched live from OpenAlex

Latar Belakang: Stunting merupakan hambatan pertumbuhan yang menyebabkan panjang badan anak tidak sesuai dengan seusianya. Keterkaitan antara kesehatan ibu hamil, pendidikan rendah, kemiskinan serta kesehatan bayi yang baru lahir sampai anak berusia dua tahun, dinilai berkaitan erat dengan kejadian stunting.Tujuan: Mengetahui hubungan karakteristik Ibu terhadap kejadian stunting pada balita di Puskesmas Muara Satu.Metode: Penelitian dilakukan pada 93 sampel Balita, dengan penelitian cross sectional. Penelitian dilakukan di wilayah kerja Puskesmas Muara Satu, dan pengumpulan data dilaksanankan pada bulan Juli 2021.Hasil: Dari penelitian, didapatkan bahwa pola asuh dan riwayat ANC, mempunyai hubungan yang sangat signifikan terhadap stunting, dengan tingkat kepercayaan 95%. Sedangkan karakteristik ibu yang lain (pendidikan, pekerjaan, penghasilan, dan ketersediaan jamban), tidak berhubungan dengan stunting.Kesimpulan: Pola Asuh dan riwayat ANC ada hubungannya dengan kejadian stunting pada anak balita, sedangkan karakteristik ibu yang tidak ada berhubungan dengan stunting adalah pendidikan ibu, pekerjaan, penghasilan dan kepemilikan jamban. Variabel yang paling dominan berhubungan dengan kejadian stunting pada balita adalah pola asuh yang baik dan riwayat kunjungan ANC lebih dari 4 kali yang dilakukan ibu di saat waktu hamil.Saran: Perlu adanya regulasi untuk pengadaan alat microtoice dan lengthboard yang digunakan sebagai upaya deteksi dini terhadap balita yang stunting ditingkat posyandu posyandu. Peningkatan dokumentasi puskesmas terhadap biodata pada anak balita. Kata Kunci : Karakteristik Ibu, Stunting, Balita ABSTRACT Background: Stunting is a growth barrier that causes a child's body length to not match his age. The relationship between the health of pregnant women, low education, poverty and the health of newborns to children aged two years, is considered to be closely related to the incidence of stunting.Objective: To determine the relationship between maternal characteristics on the incidence of stunting in children under five at the Muara Satu Health Center.Methods: The study was conducted on 93 samples of children under five, with a cross sectional study. The research was conducted in the working area of the Muara Satu Health Center, and data collection was carried out in July 2021.Results: From the study, it was found that parenting and history of ANC, had a very significant relationship to stunting, with a 95% confidence level. Meanwhile, other characteristics of mothers (education, occupation, income, and availability of latrines) were not related to stunting.Conclusion: Parenting patterns and history of ANC are related to the incidence of stunting in children under five, while maternal characteristics that are not associated with stunting are maternal education, occupation, income and latrine ownership. The most dominant variables related to the incidence of stunting in toddlers are good parenting and a history of ANC visits more than 4 times by the mother during pregnancy.Suggestions: There is a need for regulation for the procurement of microtoice and lengthboard devices that are used as an early detection effort for stunting toddlers at the posyandu posyandu level. Improvement of puskesmas documentation on biodata on children under five. Keywords: Characteristics of Mother, Stunting, Toddler

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.058
GPT teacher head0.314
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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