Abstract
Data clustering of Mitra10 member card, it is only based on the payment day by customer. And the total point only based on 0,25% calcutation of each payment. This is not so efficient knowing that there are so many ungrouping data that can be use for increase the rewards to the customer. In order to clustering the data of member card total point, it need a method of data clustering. The method election really affecting the result of data clustering. After all of the member card Mitra10 data transformed to the number form, then the datas can be grouping to fuzzy subtractive clustering algorythm. The data need to divided to some cluster : Select the amount of the cluster. In this research the data will be divided to 3 cluster. Select the center point of each cluster and fisrt center point selected randomly to generate main center point of each cluster. One data will be part of one cluster that has the smallest distance from the center cluster. Example for the first data, smallest distance get by cluster 1, so that the first data will be member of cluster 1. And so for the second data , smallest distance in cluster 3, so it will be member of cluster 3. In this iteration, center point of each cluster does not changed and there is no moving data to another cluster. Cluster 1 result: Has center (1,413, 1,195, 1,695) cluster 1 dominated by the bronze group. Cluster 2 result: Has center (2,658, 1,219, 1,585) cluster 2 dominated by the silver group. Cluster 3 result: Has center (4, 1,8, 3) cluster 3 dominated by the silver group
Highlights
it is only based on the payment day by customer
the total point only based on 0,25% calcutation of each payment
In order to clustering the data of member card total point
Summary
Konsumen adalah setiap orang pemakai barang dan atau jasa yang tersedia dalam masyarakat, baik bagi kepentingan diri sendiri, keluarga, orang lain, maupun makhluk hidup lain. Sedangkan perilaku konsumen irasional adalah suatu perilaku dalam mengonsumsi yang dapat dikatakan tidak rasional jika konsumen tersebut membeli barang tanpa dipikirkan kegunaannya terlebih dahulu. Jika konsumen memiliki kartu membership dari perusahaan retail tertentu, maka akan mendapatkan perlakuan istimewa seperti mendapat beragam hadiah, poin yang bisa ditukarkan, diskon khusus atau harga spesial. Pengelompokan (Clustering) merupakan salah satu teknik yang paling penting dalam Data Mining. Salah satu metode pengelompokan yang paling sering digunakan adalah Fuzzy C-Means. Alternatif metode pengelompokan lainnya yang dapat digunakan jika jumlah kelompok tidak diketahui sebelumnya adalah metode Fuzzy Subtractive Clustering. Teknik Data Mining yang digunakan untuk mencari segmentasi konsumen adalah menggunakan teknik clustering. Teknik clustering digunakan pada Data Mining untuk mengelompokkan 3 objek-objek yang memiliki kemiripan dalam kelas atau segmen yang sama, sementara objek-objek yang terletak pada kelas yang berbeda menunjukkan karakteristik yang berbeda juga
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