Penerapan Metode Clustering Dalam Upaya Pencegahan Penyakit Demam Berdarah Menggunakan Algoritma K-Means (Studi Kasus: Kota Tasikmalaya)

Abstract

Dengue fever is a contagious disease transmitted by the Aedes Aegypti mosquito, and this disease occurs continuously throughout the year, causing outbreaks and deaths. In Indonesia, public awareness in maintaining cleanliness and lack of anticipation of people infected with Dengue Fever, so Dengue Fever is a disease easily infected for all ages. The research methodology used in this study used the clustering method. The goal is to cluster and evaluate the k-means algorithm model to determine the algorithm's accuracy in classifying Dengue Fever disease. K-Means Clustering, K, which means a constant for the desired number of clusters, while Means which means the average of the data groups in the cluster. Therefore, research using the K-Means Algorithm will group the areas in Tasikmalaya City according to the rate of occurrence of dengue cases so that they are precisely and quickly targeted in efforts to prevent Dengue Fever. The formula used in the K-Means algorithm has four stages, namely: Determining the number of clusters, calculating distances, grouping data, and calculating the center of the cluster. The benefits of this research are that it can speed up the process of prevention efforts in Dengue Fever, know efforts to prevent Dengue fever quickly and precisely, clustering systems for prevention efforts and can reduce mortality, and add insight for readers who want to learn about clustering and K-Means algorithms.