Skripsi

IMPLEMENTASI ARTIFICIAL NEURAL NETWORKS DALAM PREDIKSI KEJADIAN OBESITAS SISWA SEKOLAH DASAR BERBASIS DATA EMOTIONAL EATING DAN POLA MAKAN

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Background: Childhood obesity has become a serious public health challenge that requires the identification of contributing factors, as pharmacological therapies are often less effective. This study aims to analyze the association between sociodemographic and behavioral factors (emotional eating, snacking habits, and family mealtime practices) and obesity among elementary school students, as well as to evaluate the performance of an Artificial Neural Networks (ANNs) model in predicting obesity. Methods: This cross-sectional study employed binary logistic regression and ANNs using the Orange software to predict obesity occurrence. Secondary data were obtained from students aged 7–12 years attending elementary schools in the Seberang Ilir and Seberang Ulu regions of Palembang. Results: Partial analysis showed that age 10–12 years (OR= 2,06; 95% CI= 1,17–3,61; p= 0,012), parental history of obesity (OR= 7,5; 95% CI= 4,18–13,45; p

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Detail Information

Series Title

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Call Number

T1867802025

Publisher

Palembang : Prodi Pendidikan Kedokteran, Fakultas Kedokteran Universitas Sriwijaya., 2025

Collation

xvi, 137 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

616.398 07

Content Type

Text

Media Type

unmediated

Carrier Type

other (computer)

Edition

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Subject(s)

Prodi Pendidikan Kedokteran
Obesitas Siswa SD

Specific Detail Info

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Statement of Responsibility

MI

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