Penerapan Algoritma K-Means Clustering Pada Penyebaran Penyakit Infeksi Saluran Pernapasan Akut (ISPA) di Provinsi Riau - Ninaria Purba; Poningsih Poningsih; Heru Satria Tambunan (Forum Kerjasama Pendidikan Tinggi (FKPT), 2021)
Health is a valuable thing for humans because anyone can experience health problems, as well as humans who are very susceptible to various kinds of diseases but we don't realize the cause. The K-means algorithm is not affected by the order of objects used, this is proven when the author tries to randomly determine the starting point of the cluster center of one of the objects at the beginning of the calculation. The resulting number of cluster membership is the same when using another object as the starting point of the center of the cluster. However, this only affects the number of iterations performed. Object clustering (object clustering) is a process of object mining which aims to partition existing objects into one or more object clusters based on their characteristics. This study examines how to use the K-means Cluster Analysis Algorithm in case studies of human infectious diseases, namely Acute Respiratory Infection. This study examines the K-means Cluster Analysis method in Acute Respiratory Infection based on a set of variables established per municipality in Riau Province