Optimization Fuzzy Geographically Weighted Clustering with Gravitational Search Algorithm for Factors Analysis Associated with Stunting
Factor Analysis on Stunting using Fuzzy Geographically Weighted Clustering with Gravitational Search Algorithm
Abstract
Stunting is a significant threat to the quality of human resources in Indonesia because stunting does not only involve physical growth disorders but can also cause children to be vulnerable to disease and experience disorders of brain development and intelligence. Many factors cause stunting, not only malnutrition in pregnant women and toddlers. Grouping can be done to make it easier to see the characteristics of the factors causing stunting in Indonesia. The grouping is done based on the similarity of the characteristics of the factors causing stunting in each province. This study used Fuzzy Geographically Weighted Clustering (FGWC) with Gravitational Search Algorithm (GSA) to group and assess the best cluster using the Partition Coefficient validity index, Classification Entropy, Separation Index, Xie & Beni's Index, and IFV Index. Furthermore, a difference test was conducted to determine the dominant factor causing stunting in the formed cluster. The results showed that the FGWC-GSA gave the best clustering results on the fuzziness value of 2 with the number of clusters 2. Cluster 1 consisted of 16 provinces, and cluster 2 consisted of 18 provinces. Based on the T-test, the variables of infants who received exclusive breastfeeding had significant differences between clusters. Therefore, cluster 2 is a cluster that has dominant problems related to exclusive breastfeeding.
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