Analysis of Malnutrition Status in Toddlers Using the K-MEANS Algorithm Case Study in DKI Jakarta Province
Year: 2024
Type: article
Abstract: Malnutrition in children is a serious health issue in various regions, including DKI Jakarta Province, which affects the physical and cognitive development of children. This research aims to classify malnutrition status in children using the K-Means algorithm, focusing on cases in DKI Jakarta. The objective is to identify patterns of malnutrition prevalence across different regions, serving as a basis for more effective interventions. The data used in this study includes the percentage of children with severely stunted, stunted, and normal nutritional status across six districts/cities in DKI Jakarta. The results of K-Means clustering show that Central Jakarta has the highest prevalence of severely stunted (10.50%) and stunted (13.01%) status, while West Jakarta has the lowest prevalence of severely stunted (4.62%) and stunted (10.22%) status. The solution offered by this research is the grouping of regions based on malnutrition prevalence, allowing for the identification of areas requiring priority intervention. The analysis results indicate that DKI Jakarta can be classified into several clusters based on malnutrition prevalence. The cluster with the highest malnutrition prevalence includes Central Jakarta, while the cluster with the lowest malnutrition prevalence includes West Jakarta and the Thousand Islands. The implementation of K-Means in this research provides an efficient approach to identifying groups of regions that need more attention in combating malnutrition in children. In conclusion, this research can serve as an important reference for policymakers in formulating more effective and efficient intervention strategies in DKI Jakarta, as well as inspire similar studies in other regions with different population characteristics
Source: SinkrOn
Institution: Universitas Bina Sarana Informatika
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $32
OpenAlex ID: W4404373255