TESTING K-MEANS ALGORITHM USING THE RAPID MINER APPLICATION FOR DATA GROUPING
| Main Authors: | Sembiring, Ade Setiawan, Panjaitan, Suprianto, Pakpahan, Aditiya |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | eng |
| Terbitan: |
Sean Institute
, 2019
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| Subjects: | |
| Online Access: |
http://infor.seaninstitute.org/index.php/infokum/article/view/26 http://infor.seaninstitute.org/index.php/infokum/article/view/26/16 |
Daftar Isi:
- Data mining is a technique of extracting information that has not been known before in a collection of data in the database. Data mining has been applied in various fields that require information extraction. One of them is in grouping data. Grouping is used to divide a set of data into several useful parts so that it is easier to identify the class of data. Distribution companies can use grouping, one of which is to determine the intensity of the volume of goods ordered. This study analyzes the application of data mining with the k-means clustering algorithm to extract information from random goods ordering data. Namely by using the number of items and the total amount of the quantity of each item ordered. Then it is implemented into a website-based system to make it easier to get valid information.