KLASTERISASI INDEKS PEMBANGUNAN MANUSIA (IPM) PER KABUPATEN DI INDONESIA DENGAN MENGGUNAKAN ALGORITMA K-MEANS - Akhmad Budi (Institut Bisnis dan Informatika Kwik Kian Gie, 2016)
Development of technology and information systems use data mining as a method of data processing is growing, due to the large amount of data available and growing every day, especially economy, health, and education data. One of the benefits that can be obtained by applying information technology, among others, is to conduct the analysis and clustering of large amounts of data. The human development index (IPM) is a factor of public welfare measurement in Indonesia, but quite difficult to analyze because there has not been a proper measurement clustering method for cluster the data (IPM) in the future. This research aims to make it easier to read the data and classifying data by using K-Means. With the aim of obtaining the results of the cluster so as to facilitate reading the index.Key Words : Clustering, Human Development Index, Data Mining, K-Means, Rapidminer