Penerapan Metode Algoritma K-means Dalam Pengelompokan Angka Harapan Hidup Saat Lahir Menurut Provinsi - Riska Oktavia; Jaya Tata Hardinata; I Irawan (LPPM STIKOM Tunas Bangsa, 2020)
Life Expectancy (AHH) at birth estimates the average additional age of a person from a mother's womb during the birth process, which is expected to be able to live normally and healthy. Based on data obtained from the Government's official website address at https://bps.go.id/, which displays several amounts that vary from 2015 to 2018 according to the Province in Indonesia. For this reason, it is necessary to cluster each number of life expectancy at birth with the number from the lowest to the highest using the Data Mining method with the K-means Clustering Algorithm. In this research technique, the data will be classified based on the Province's name, which has the number of Life Expectancy at birth from 2015 to 2018. That is why the Data Mining method is used to facilitate data grouping on the number of Life Expectancy at birth according to the name of the Province in Indonesia. After grouping, the results will be obtained the number of Life Expectancy at birth, and grouping starts from the lowest to the highest cluster. In the research that has been carried out, it is expected that the Government will provide solutions of the highest life expectancy at birth that has the highest number so that in the following year, the life expectancy rate will be reduced.