@thesis{thesis,
		author={Arianto  Rakhmat and HASSAN  MUHAMAD ALWI and Putra  Rakhmadi Irfansyah},
		title ={KLASTERISASI KEMIRIPAN JUDUL BERITA PALSU PADA BERITA DARING MENGGUNAKAN METODE FUZZY C-MEANS},
		year={2019},
		url={http://156.67.221.169/4478/},
		abstract={This study discusses the making of the application of the clustering of Similar
News Title Clusters based on the News Title dataset sourced from
turnbackhoax.id. to identify online news titles that are false or valid using the
Fuzzy C-Means (FCM) method. Fuzzy C-Means has a high degree of accuracy
and fast computing time. Fuzzy C-Means can be used to classify data based on
certain attributes. Before in to the FCM, the pre-processing stage with the textmining method is to convert text data into numerics to make it easier when used
as input parameters into the FCM method which includes tokenizing, filtering, and
stemming. Then do the calculation of the number of occurrences of words / term
queries in the document being tested and used as input parameters for the
calculation of the FCM method. In this study, the Fuzzy C-Means algorithm will
be used to cluster the similarity of fake news titles on scattered online news. From
the results of the cluster that has the highest value becomes an additional
parameter to identify hoaks or valid news. The testing method uses accuracy by
calculating what percentage of documents are similar to the news headline input
and have an accuracy rate of 64%.}
		}