Analisis Pengelompokan Konsumsi Kalori Berdasarkan Provinsi di Indonesia Menggunakan Algoritma K-Means

Abstract

This research aims to identify calorie consumption patterns in Indonesia and analyze them using the k-means clustering method. This research uses calorie consumption data in 34 Indonesian provinces, which are then divided into three clusters: low cluster with 8 provinces, medium cluster with 4 provinces, and high cluster with 22 provinces. The main objective is to identify differences in calorie consumption patterns between these three clusters. It is hoped that the results of this research will provide better insight into calorie consumption patterns in Indonesia and enable more effective decision making regarding national nutrition policy. The main problem faced in this research is how to group provinces into appropriate clusters and how to analyze calorie consumption patterns in each cluster. This research uses Rapid Miner software to carry out data analysis and clustering.