Research Article
Implementation Of K-Means Clustering Algoritm To Determine Stunted Status In Children Under Two Years Old
@INPROCEEDINGS{10.4108/eai.18-10-2019.2289979, author={Petrisia Widyasari Sudarmadji and Christa Elena Blandina Bire}, title={Implementation Of K-Means Clustering Algoritm To Determine Stunted Status In Children Under Two Years Old}, proceedings={Proceedings of the 1st International Conference on Engineering, Science, and Commerce, ICESC 2019, 18-19 October 2019, Labuan Bajo, Nusa Tenggara Timur, Indonesia}, publisher={EAI}, proceedings_a={ICESC}, year={2019}, month={12}, keywords={stunting k-means antropometri clustering}, doi={10.4108/eai.18-10-2019.2289979} }- Petrisia Widyasari Sudarmadji
Christa Elena Blandina Bire
Year: 2019
Implementation Of K-Means Clustering Algoritm To Determine Stunted Status In Children Under Two Years Old
ICESC
EAI
DOI: 10.4108/eai.18-10-2019.2289979
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