ANALISIS KLASTER DENGAN AVERAGE LINKAGE METHOD DAN K-MEANS METHOD UNTUK PENGELOMPOKAN KABUPATEN/KOTA BERDASARKAN KASUS PENYAKIT PADA BALITA DI PROVINSI SUMATERA SELATAN
Daftar Isi:
- This study uses two cluster analysis methods, namely Average Linkage Method, and K-Means Method. These method are used to classify 17 districts/cities in South Sumatera Provinces in 2015 based on 6 cases of diseases occurring in children including pneuomia toddlers, diarrhea , Dengue, malnutrition, measles and polio. The best method is the method with the smallest standart deviation ratio value. Average Linkage Method and K-Means Method almost similar form 3 clusters.Average Linkage Method yields Cluster 1 consists of 12 districts of Banyuasin Regency, Empat Lawang, Pagar Alam City, East OKU, PALI, MUBA, Palembang City, Muratara, Prabumulih City, and Ogan Ilir, Musi Rawas with high pneumonia infants cases and low incidence of diarrhea, measles and malnutrition. Cluster 2 consists of 4 districts of OKI, OKU Selatan, OKU, Lahat, and Lubuk Linggau with cases of polio and malnutrition and high cases of dengue. Cluster 3 consists of 1 districts of Muara Enim with cases of diarrhea and high cases of measles, pneumonia infants, dengue, and polio are low. Different with Average Linkage Method, District Lubuk Linggau belongs to cluster 2 in the result of K-Means Method. Based on the standard deviation ratio value, K-Means Method clustering results have a standard deviation ratio value of 0.31 is better than Average Linkage Method which has a standard deviation ratio value of 1.25.