PENERAPAN FUZZY C-MEANS PADA KLASTERISASI KARAKTERISTIK PENGUNJUNG WEBSITE PMB STT – PLN UNTUK MENINGKATKAN KEPADATAN KUNJUNGAN

Abstract

Bringing high website visitors is a difficult challenge to face because of the many interesting website
contents popping up. This problem is also faced by the STT-PLN New Student Admission (PMB)
website. One of the things that need to be considered in increasing website visitors is by knowing the
demographic data of visitor characteristics. Changes in behaviour are also caused by the attractiveness
of quality content that can attract visitor interest and can improve SEO (Search Engine Optimization)
to be able to gain visitor density (traffic) so that it is easily indexed by Google's search engine. The data
used in this study are location data, web browser data, parent attraction data and teenage attraction
data of visitors to the PMB STT-PLN website. The method that can be done is to cluster the demographic
characteristics of visitors using Fuzzy C-Means and Root Mean Square Error to test the accuracy of
the cluster. Optimal accuracy results obtained for each data are when the browser data is grouped into
4 clusters with an error value of 0.000275229, location data into 2 clusters with an error value of
0.003197591, teenage attractiveness data into 4 clusters with an error value of 0.000322929, and data
the appeal of parents into 2 clusters with an error value of 0.084997533.