JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 6, No 1 (2022): Januari 2022

Penerapan Data Mining Dalam Pemilihan Produk Unggulan dengan Metode Algoritma K-Means Dan K-Medoids

Reza Gustrianda (Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Jakarta)
Dadang Iskandar Mulyana (Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Jakarta)



Article Info

Publish Date
25 Jan 2022

Abstract

As a business company, PT. XYZ Indonesia is committed to always make improvements to all aspects such as, in terms of determining superior products. To be able to do this, it requires a sufficient source of information to be able to analyze what products are superior or in high demand and what products are less desirable. To find out what products enter the superior product cluster, then researchers do product grouping using the clustering method. In the clustering method there are two types of cluster analysis that have interrelated algorithms, namely k-means and k-medoids. The result of research already conducted that from the value of Davies Bouldin to the k-means algorithm is -0.430 and from the value of Davies Bouldin k-medoids is -1,392 which means that the Davies Bouldin value for the k-medoids method has the smallest Davies Bouldin value so the grouping results using the k-means method are more appropriately used on the issue of superior product selection.

Copyrights © 2022






Journal Info

Abbrev

mib

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer ...