GROUPING THE DEVELOPMENT OF PRICES OF BUILDING STAPLES IN BINJAI CITY BASED ON THE TYPE OF GOODS USING THE CLUSTERING METHOD
(Case Study: BPS Kota Binjai)
Keywords:
Harga Bahan Bangunan, Data Mining, K-Means.Abstract
The development of basic commodity prices is essentially a physical development activity. Various kinds of resources are processed with the power of human resources. The longer the processing process, the greater the added value for humans and the greater the costs required. One of the most widely used methods in the clustering method is to use the K-Means algorithm. K-Means is a non-hierarchical (block) grouping method that seeks to partition data into clusters/groups so that data with the same characteristics will be included in the clustering method. in the same cluster and data with different characteristics are grouped into another group. From the 20 data obtained 3 groups, Cluster 1 has 7 data, Cluster 2 has 6 data, and Cluster 3 has 7 data. And the most group obtained is cluster 1 and cluster 3.Cluster 1 contains 7 data, namely types of bricks with a fixed price of IDR 200 per piece in 2020 South Binjai. Cluster 2 contains 6 data, namely types of bathtub items with a fixed price of IDR 75,000 in 2020 South Binjai. Cluster 3 contains 7 data, namely the type of emulsion paint with a fixed price of IDR 300,000 in 2020 South Binjai.
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