Penerapan Data Mining Dalam Mengelompokkan Data Impor Tembaga Menurut Negara Asal Menggunakan Algoritma K-Means

Lise Pujiastuti, Mochamad Wahyudi, Solikhun Solikhun

Abstract


Import is an activity of transportation of goods or commodities from country to country. The import process is generally the activity of entering goods or commodities from other countries into the country. Copper is one of the most important metals and plays a major role in human history and is among the first mined metals. Copper is a good conductor of heat and electricity. In addition this element has a very fast corrosion. Pure copper is smooth and soft, with a reddish orange surface. Copper import activity from year to year continues to increase. There needs to be a deep presentation regarding copper imports. In this study, the authors use the data mining technique k-means clustering method to classify copper import data according to the original destination. The results of this study are a copper import data cluster. Copper import clusters consist of two clusters namely high and low clusters. High clusters are from Japan and China, while low clusters consist of South Korea, Thailand, the Philippines, Australia, Malaysia, Singapore, Myanmar and Chile.

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DOI: http://dx.doi.org/10.30645/senaris.v2i0.191

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