Anton, Jefrintus Antianus (2021) Implementasi Algoritma K-Means Clustering dalam Pengelompokan Barang Konveksi. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT Based on the data from the sale of convection at the Yasinta Gloria Store, where the existing data shows that several items were sold in large quantities, a system is needed that can classify goods based on sales data. Grouping data on convection goods based on sales data is carried out so that the data used can produce useful information for business owners / convection shops so that errors in data recording do not occur because they reduce the effectiveness of working time. Convection business owners find it difficult to find information from unprocessed sales data where the data is useful in grouped goods manufacturing reports. From this background, a computerized information system is needed to support the flow of data and information in accordance with the needs of the process. The problem to be studied is related to the sales data processing process on how to produce useful information and knowledge through data mining software, namely using the K-Means algorithm with the Clustering method on sales data from the Yasinta Gloria Store. Convection sales data is expected to help manage businesses in analyzing and classifying the convection products sold. That is, business owners who can be accessed by which groups are sold, and can assist business owners in making decisions in purchasing goods for the future. Where the results of the grouping system produce 20 items with high sales volume, and 10 items with low sales. Based on manual calculations and testing systems, using the Clustering method with the K-Means algorithm can be used to determine the group of goods on convection sales. Keywords: Clustering, K-Means Algorithm, Sales, Convection Goods
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 23 Mar 2021 03:12 |
| Last Modified: | 23 Mar 2021 03:12 |
| URI: | http://eprints.uty.ac.id/id/eprint/7082 |
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