Fuzzy C-Means Algorithm for Clusterization of Credit Card Usage

Miftahul Jannah (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Melani Nur Mudyawati (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Acep Razif Andriyan (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Dinda Meysya Rochma (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Siti Lufia Dwi Agustini (Teknik Informatika, UIN Sunan Gunung Djati Bandung)

Gunung Djati Conference Series
Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020

Credit cards are now familiar to the public. A credit card is a means of payment in lieu of cash in the form of a card issued by the bank to facilitate transactions for customers. Currently, there are various kinds of credit card issuing financial service companies in the world, including Indonesia. With various benefits so that credit is loved by all groups, so that everyone competes to use credit by choosing the desired bank. Data mining methods can provide solutions to extract knowledge from data by looking for certain patterns or rules from large amounts of data. One of the data mining methods is clustering, in which clustering is used to group data by grouping the data into several clusters. By using the credit card data set is divided into 3 clusters using the Fuzzy C-Means algorithm. Of the 3 clusters, the ones that are prioritized with the largest value are the clusters that are widely used by many people, which have a medium value, while the cluster with the smallest value is the cluster with the least interest.