ANALISIS PENGELOMPOKKAN STATUS GIZI ANAK DAN REMAJA WARGA DESA LEGOK KECAMATAN GEMPOL KABUPAEN PASURUAN MENGGUNAKAN METODE K MEANS

Penelitian ini bertujuan menganalisis dan mengelompokkan data status gizi anak-anak dan remaja di Desa Legok, Kecamatan Gempol, Kabupaten Pasuruan menggunakan metode K-Means. Data dikategorikan menjadi lima kategori gizi, yaitu "Gizi buruk (severely thinness)", "Gizi kurang (thinness)", "Gizi baik (normal)", "Gizi lebih (overweight)", dan "Obesitas (obese)" berdasarkan atribut umur, tinggi badan, dan berat badan. Dengan memanfaatkan web sebagai alat uji baru, diharapkan pengelompokkan data gizi menjadi lebih efisien dan mudah diakses untuk mendukung perencanaan dan intervensi gizi yang tepat.
Metode penelitian ini menggunakan K-Means untuk mengelompokkan data status gizi anak-anak dan remaja berdasarkan atribut umur, tinggi badan, dan berat badan. Data diinisialisasi dengan bobot sesuai kategori gizi. Pengguna memasukkan data atribut umur, tinggi badan, dan berat badan melalui formulir pada sub menu implementasi web. Setelah iterasi K-Means, hasil pengelompokkan disajikan dalam bentuk grafik dan visualisasi yang interaktif.
Hasil penelitian menunjukkan variasi distribusi status gizi anak-anak dan remaja di Desa Legok. Mayoritas data masuk dalam kategori "Gizi baik (normal)", namun terdapat data yang termasuk dalam kategori gizi yang kurang baik. Hasil ini menjadi dasar bagi pengambilan keputusan dan perencanaan
program intervensi gizi yang efektif untuk meningkatkan kualitas gizi dan kesehatan anak-anak dan remaja di Desa Legok.
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This study aims to analyze and classify data on the nutritional status of children and adolescents in Legok Village, Gempol District, Pasuruan Regency using the K-Means method. The data were categorized into five nutritional
categories, namely "severely thinness", "thinness", "good nutrition (normal)", "overweight" and "obese" based on the attributes of age, height and weight. By utilizing the web as a new test tool, it is hoped that the classification of nutrition data will become more efficient and easily accessible to support appropriate nutrition planning and interventions.
This research method uses K-Means to classify data on the nutritional status of children and adolescents based on the attributes of age, height and weight. The data is initialized with the weight according to the nutrition category. The user enters data on the attributes of age, height and weight through a form on the web implementation sub menu. After the K-Means iteration, the grouping
results are presented in the form of interactive graphics and visualizations.
The results showed variations in the distribution of the nutritional status of
children and adolescents in Legok Village. The majority of the data fall into the
category of "good nutrition (normal)", but there is data that falls into the category
of poor nutrition. These results form the basis for decision making and planning
of effective nutrition intervention programs to improve the quality of nutrition and
health of children and adolescents in Legok Village.
The results showed variations in the distribution of the nutritional status of children and adolescents in Legok Village. The majority of the data fall into the category of "good nutrition (normal)", but there is data that falls into the category of poor nutrition. These results form the basis for decision making and planning of effective nutrition intervention programs to improve the quality of nutrition and health of children and adolescents in Legok Village.