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T.M Diansyah
Universitas Harapan Medan
Computer Science & IT Library & Information Science

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Penerapan Data Mining K-Means Clustering Untuk Pengelompokan Barang Pada Masa Pandemi Covid-19 Di Rex Indonesia Sisca Dwivayana; T.M Diansyah; Divi Handoko
SEMINAR NASIONAL TEKNOLOGI INFORMASI & KOMUNIKASI Vol. 1 No. 1 (2021): Prosiding Snastikom 2021
Publisher : Universitas Harapan Medan

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Abstract

Freight forwarding services are very useful and very easy to access, since the implementation of working from home a lot of workers, housewives, or traders, many of whom use delivery services both to meet their needs and for the business of buying and selling goods. Royal Express Indonesia (REX) is a company that focuses on its services as a delivery service company. The cases COVID-19 are increasing and spreading rapidly throughout Indonesia. By grouping the types of packets using the K-Means algorithm. Can assist companies in evaluating the statistics of goods that have increased and decreased. The application of the method K-Means will be carried out using SPSS version 25 software. The results of the K-Means Clustering process can be concluded that cluster 1 has 8,000 (53.33%) data, cluster 2 has 4,000 (26.67%) data and cluster 3 has 3,000 (20.00%) data.
Co-Authors Divi Handoko Sisca Dwivayana