Implementation Of K-Means Clustering Algoritm To Determine Stunted Status In Children Under Two Years Old

Abstract

The stunting prevalence in Indonesia ranks fourth in the world, meaning that 37% of Indonesian toddlers are stunted. Stunting is a chronic nutritional deficiency problem caused by lack of nutritional intake for a long time, resulting in a disturbance to the child's growth, which is a lower or shorter child (dwarf) than the standard of his age, Especially in the first thousand golden age of life. The first thousand days of life is counted from the 9 months of a child in terms of mothers up to 2 years of life (0-23 months). The Data on the basic health Research (RISKESDAS) in 2018 shows the prevalence of stunting in the national sphere of 30.8%, consisting of a short prevalence of 19.3% and very short at 11.5%, and the highest percentage in 2018 is in Nusa Tenggara province. Eastern (42.6%). NTT ranked first in the province for stunting status and the parameters used to determine stunting status are based solely on the age of weight (BB/U), which is on the card to the Healthy (KMS). The urgency of the problem, is to classify the stunting status specifically based on the standard characteristics of the WHO use the K-means Clustering algorithm. The objective of the study is to obtain the classification results with the algorithm method of the Clustering K-means in determining the stunting status in children under the age of two years. The method of implementing this research is CRISP-DM (Cross Industry Standard Process for Data mining) model.

Information System for Evaluating Specific Interventions of Stunting Case Using K-means Clustering

“…One form of chronic malnutrition that lasts for a long time due to failure to meet nutrition in infants is called stunting [1]. Stunting not only interferes with physical growth but more than that, stunting also interferes with brain development which can affect cognitive abilities, productivity and creativity [2]. Regional Health Research (RISKESDAS) in 2018 noted that Indonesia has a stunting prevalence rate of 30.8%, where the WHO annual target is no more than 20% [3].…”

“…The results of the study stated that 48% of infants experienced severe stunting, 22% of infants experienced stunting, 28% of normal infants and 2.5% of infants experienced abnormal. With 70% value of the accuracy of k-means clustering [2]. Further research with complex health data has been carried out to determine the right algorithm in getting the optimal group.…”