Penerapan Metode K-Means Clustering Untuk Analisa Penjualan Komoditas Toko Tani Indonesia

Abstract

Thisreportdescribesthegroupingofagriculturalcommodities.AgriculturalCommoditiesaretheresults of farming activities that can be traded, stored and exchanged. In carrying out testing ofthis algorithm, the data used is goods data at the Indonesian Farmer Center shop. In thisapplication, clustering is used using the K-means algorithm. From the data that was processedwith data samples taken at the Indonesian farmer's shop center, three types of data groups wereproduced. Namely low sales data, medium sales data, and high sales data. So that with this datagrouping, the Indonesian farm shop can find out the types of goods that are selling well andwhichare not. Sothatthe goods in the warehousedo notaccumulate.