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

Abstract

One of the causes of death of children under five is chronic malnutrition or stunting. The government has made a policy as an effort to reduce stunting. Specific intervention nutrition programs are activities that directly address the occurrence of stunting. Evaluation of edit interventions that have currently been carried out but have not separated the process based on intervention indicators so that it results in a long processing time and large exit costs so we need a system that can accelerate the process of evaluating specific interventions. Information systems for evaluating specific interventions can be a solution to this problem. In this study, an information system for evaluating specific interventions of stunting cases was developed web-based to facilitate real-time operation. The evaluation information system is designed to collect national data and carry out a clustering process using the k-means method and evaluation stucture cluster using silhouette method. In this study an evaluation value of 34 provinces was obtained which was divided into several clusters as a result of evaluation process in the information system.

Optimization Fuzzy Geographically Weighted Clustering with Gravitational Search Algorithm for Factors Analysis Associated with Stunting

“…Research on the clustering of stunting data was conducted by Seifu Hagos Gebreyesus et al [8], who conducted a cross-sectional study to evaluate the clustering of stunting factors in the southern Ethiopian area using logistic regression. In addition, Widya Sartika, Suryono, and Adi Wibowo [9] developed an information system to evaluate the factors that cause stunting in real-time using the k-means method. This research uses simple and unmodified clustering methods.…”