Perancangan Data Mining Untuk Menentukan Tingkat Kelarisan Sparepart Mobil Pada Bengkel Andesco Menggunakan Metode Clustering Dengan Algoritma K-Means Berbasis Web - Teri Ade Putra (Universitas Pahlawan Tuanku Tambusai, 2018)
The growing competition in the business world, especially in the workshop industry and auto spare parts sales requires developers to find a pattern that can increase sales and marketing of goods in the workshop, one of which is the utilization of transaction data. At Andesco Motor manager lacking in reviewing products sold, products of what is needed consumer and data storage is less effective. In this analysis used the application Clustering using K-Means algorithm. Clustering is a technique of one of the functionalities of data mining, clustering algorithm is an algorithm of grouping a number of data into groups of certain data (cluster). So with the grouping of this data can determine the Andesco Motor selling goods and slow-moving. Warehouse so that the items do not accumulate. With the design of data mining application that is displayed in the form of websites using PHP with a MySQL database program is expected to provide real solutions to Andesco Motor in order to find out which items are selling and where the goods are not selling.Keywords: Data Mining, Clustering, K-Means algorithm, PHP MySQ