Penerapan Sistem Informasi Deteksi Stunting Dengan Menggunakan K-means Clustering Berbasis Web

Penulis

  • M. Tri Buana Nugraha Universtas Pembangunan Panca Budi
  • Fachrid Wadly Universtas Pembangunan Panca Budi
  • Nadya Andhika Putri Universtas Pembangunan Panca Budi

Kata Kunci:

stunting, early detection, K-means clustering, web-based information system, nutritional status of toddlers

Abstrak

Stunting is a serious problem in the field of child health in Indonesia caused by chronic malnutrition, especially in the first 1,000 days of life. To overcome this problem, an efficient and accurate early detection method is needed to accelerate intervention. This study aims to develop a web-based information system that is able to group toddler data and identify potential risks of stunting using the K-means clustering algorithm. The system was developed with a waterfall approach and uses anthropometric attributes such as weight, height, age, and gender as clustering parameters. The grouping results are displayed in the form of tables and graphic visualizations to facilitate analysis. This system is designed to be easily accessible to health workers and policy makers, so that it can support more targeted decision making in efforts to overcome stunting.

Unduhan

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Referensi

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Unduhan

Diterbitkan

31-07-2025

Cara Mengutip

M. Tri Buana Nugraha, Fachrid Wadly, & Nadya Andhika Putri. (2025). Penerapan Sistem Informasi Deteksi Stunting Dengan Menggunakan K-means Clustering Berbasis Web. Jurnal Nasional Teknologi Komputer, 5(3), 811–822. Diambil dari https://publikasi.hawari.id/index.php/jnastek/article/view/278

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