Open AccessFUZZY C-MEANS CLUSTERING UNTUK PENGELOMPOKAN BAHAN MAKANAN BERDASARKAN KANDUNGAN ZAT GIZI
Author(s) -
Meysi Budiyanti,
Mutia Nur Estri
Publication year - 2012
Publication title -
jurnal ilmiah matematika dan pendidikan matematika (jmp)/jurnal ilmiah matematika dan pendidikan matematika
Language(s) - English
Resource type - Journals
eISSN - 2550-0422
pISSN - 2085-1456
DOI - 10.20884/1.jmp.2012.4.1.2958
Subject(s) - cluster analysis , cluster (spacecraft) , fuzzy logic , fuzzy clustering , mathematics , point (geometry) , data mining , computer science , statistics , artificial intelligence , geometry , programming language
Fuzzy C-Means Clustering (FCM) is a data clustering technique where each data point belongs to a cluster by membership degree. FCM starts with the concept of cluster centers that mark the mean location of each cluster. By iteratively updating the cluster centers and the membership degree for each data point, then the cluster centers move to the right location. FCM can be applied to group the nutrients of foods based on three functions of nutrients which are food as energy provider, body functions regulator and growth developer. Each nutrients are grouped into three cluster. The information of food group can used as reference or recomendation for someone who