Putri, Seravina Ade (2023) Analisis Perbandingan Algoritma Clusteringdengan Metode Shilloutte Index Untuk Pemetaan Status Gizi Balita Di Posyandu Kelurahan Gadang Kota Malang. Undergraduate thesis, Fakultas Teknologi Informasi Universitas Merdeka Malang.

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Abstract

The problem of nutritional status in toddlers is still a major problem that needs attention, one of which is malnutrition. The problem of nutritional status in toddlers is directly caused by insufficient food intake, economic factors, and
inadequate families. The purpose of this study was to compare the clustering algorithms k-means and fuzzy c-means with the Shilloutte index method for mapping the nutritional status of toddlers in general so that it can be used as a basis for prevention so that the health of toddlers in posyandu kelurahan gadang kota malang remains safe and avoids malnutrition status in toddlers. This study uses seven parameters, namely the name of the toddler, age, height, weight, BMI valid use ,and nutritional status of toddlers, and uses the silhouette index validation calculation to measure the resulting cluster cohesiveness. From the results of the
cluster analysis, the k-means algorithm gets a validation result of 0.553 using 4 clusters and the fuzzy c-means algorithm gets a validation result of 0.187 using 4 clusters. Of the two comparisons, the k-means algorithm gets the best validation because it gets the highest validation compared to the fuzzy c-means algorithm

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