PERBANDINGAN PENGKLUSTERAN DATA IRIS MENGGUNAKAN METODE K-MEANS DAN FUZZY C-MEANS
ABSTRACT: Indonesia with
abundant natural resources, certainly have a lot of plants are innumerable. To
clasify the plants into different clusters can use several methods. Methods
used are K-Means and Fuzzy C-Means. However, this methods have difference. Not
only in terms of algorithms, but in terms of value calculation on the root mean
square error (RMSE) also different. To calculate the value of RMSE there are
two indicators are required, namelt the training data and the checking data. Of
discussion, the Fuzzy C-Means method has RMSE values smaller than the K-Means
method, namely on 80 training data and 70 checking data with RMSE value
2,2122E-14. This indicates that the Fuzzy C-Means method has a higher level of
accuracy than the K-Means method
Penulis: Fitria Febrianti,
Moh. Hafiyusholeh, Ahmad Hanif Asyhar
Kode Jurnal: jpmatematikadd160374
