Skripsi

PREDIKSI RISIKO OBESITAS PADA DEWASA MUDA MENGGUNAKAN MACHINE LEARNING METODE DECISION TREE

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Penilaian

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Introduction : Obesity has been designated as a global epidemic due to its increasing prevalence. Obesity is a complex health problem with limited understanding of risk factors. The purpose of this study is to apply, analyze, and evaluate a Machine Learning algorithm, the Decision Tree in predicting obesity in young adults. Method : This type of research is analytic observational with a cross sectional study design. This study is a secondary study. The sample in this study were young adults (20-39 years old) who visited one of the health centers in Palembang City, with a minimum sample size of 262. Univariate and bivariate analysis using SPSS and multivariate using Machine Learning Decision Tree. Results : The total sample was 971 people with the results of 581 people (59.8%) being obese, the majority of respondents were female (73.7%), and the majority of samples aged 35-39 (45%). The results of the analysis with chi-square obtained a significant relationship in the variables of age, gender, and physical activity with a p-value

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407000189	T137027	T1370272023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1370272023

Publisher

Inderalaya : Prodi Pendidikan Dokter, Fakultas Kedokteran Universitas Sriwijaya., 2023

Collation

xvii, 71 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

616.390 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Obesitas/kegemukan
Prodi Pendidikan Dokter

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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