Nutritional Status Classification of Toddlers Using K-Nearest Neighbor Algorithm

  • Nur Amanda Pratiwi Informatics; Universitas Bhayangkara Jakarta Raya
  • Prima Dina Atika Universitas Bhayangkara Jakarta Raya
  • Herlawati Herlawati Universitas Bhayangkara Jakarta Raya http://orcid.org/0000-0002-4815-9841
Keywords: euclidean distance, k-nearest neighbor, nutritional status, posyandu

Abstract

Nutrition is important for the balance of the human body. Knowing the nutritional status is very important to realize the good and the quality human resources. Posyandu Parkit is one of the many Integrated Healthcare Center (posyandu) in Indonesia that provides health services for the community, one of which is monitoring and nutritional development of toddlers. However, the Posyandu Parkit in determining the nutritional status of toddlers is done manually; this method uses measurement parameters based on body weight (BB/U) which are less specific in showing the nutritional status of the toddler by matching manually with a reference standard table available in a healthy card (KMS). The purpose of this research is to produce a website that can determine the nutritional status of toddlers quickly and accurately. The system is designed using the K-Nearest Neighbor method which is a classification method. The K-Nearest Neighbor process is carried out by calculating the distance between the test data and the training data using the Euclidean distance formula, before sorting from the closest distance to the k-th order, then nutritional status is determined. The results of this study are a website that can determine the nutritional status of toddlers by applying the K-Nearest Neighbor algorithm with BB/U, TB/U, and BB/TB accuracies were 93.75%, 87.5%, and 93.75 %, respectively.

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Published
2022-09-27