Data Mining Klasterisasi dengan Algoritme K-Means untuk Pengelompokkan Provinsi Berdasarkan Konsumsi Bahan Bakar Minyak Nasional - Arief Wibowo; Indah Rizky Mahartika (Prosiding SISFOTEK, 2019)
Petroleum is one of the natural resources that play an important role in human life, mainly used as the fuel needed by all levels of society. The distribution of fuel oil (BBM) in Indonesia is carried out by the Downstream Oil and Gas Regulatory Agency (BPH Migas). With the availability of data on fuel consumption in each province, it can be seen that the pattern of fuel consumption in Indonesia is beneficial for regulators in the management of fuel distribution. To find out the pattern of national fuel consumption, we need a model of grouping regions in Indonesia based on the level of fuel consumption in each province. This study analyzes data on national fuel consumption throughout Indonesia using the Data Mining Clustering technique, and the Euclidean Distance measurement method. The final results of this study indicate that the K-Means algorithm can group provinces based on national fuel consumption levels into three clusters with their respective specifications. Modeling results were evaluated using the Davies Bouldin Index (DBI) instrument, with a value of 0.32. The results of testing using DBI approaching 0 indicate that the clusters formed are relatively very good and ideal.