Laporkan Masalah

MODIFIKASI ALGORITMA FUZZY C-MEANS CLUSTERING (Studi Kasus : Pengelompokkan Propinsi Berdasarkan Kualitas Pendidikan Madrasah); A MODIFIED FUZZY C-MEANS CLUSTERING ALGORITHM (Case Study : Provincial Groupings Based on the Quality of Madrasah Education)

Muhammad Fajeri, Subanar

2011 | Disertasi | PROGRAM STUDI S-2 MATEMATIKA

uzzy C-Means (FCM) is a data clustering technique where the existence of each data point in a cluster is determined by the degree of membership that is on the interval [0,1]. One of the deficiencies that exist in the classical FCM method is that the membership of a data value to a particular cluster depends directly to the membership value of the data on another cluster, this is caused by the constraint functions it has. Several new algorithms are developed to improve the performance of the FCM, including the Adaptive Fuzzy Clustering (FAC) and the Modified Fuzzy CMeans (MFCM). Meanwhile, a measuring tool used to evaluate the performance of clustering methods is to use the ratio of standard deviation in the group and the standard deviation between groups. Based on the results of grouping by using the data quality of madrasa education, it turns out that MFCM method has better performance when compared with the other two methods

Kata Kunci : Analisis Kelompok, Fuzzy Clustering, Fuzzy C-Means, Fuzzy Adaptive Clustering, Modifikasi Fuzzy C-Means, Kualitas Pendidikan Madrasah


    Tidak tersedia file untuk ditampilkan ke publik.