SETIADI, CANDIKA SILAI PRAHMA (2024) CLASSIFICATION OF GOODS TURNOVER RATE USING K-MEANS CLUSTERING METHOD. Tugas Akhir thesis, Informatics.
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Abstract
ABSTRACT CV ESIA INDORAYA is a distributor company that sells products such as credit, internet quota and starter cards. Currently, CV ESIA INDORAYA is still fulfilling stock of goods or products and recording transactions manually, so errors often occur in recording goods turnover data in retail. CV ESIA INDORAYA in the system that is currently running cannot group products that are bestsellers and those that are not bestsellers. So it is necessary to process big data using the K-Means Clustering method. In this research, the data used comes from retail goods turnover data at distributors in the form of RFM (recency, frequency, monetary) data. The K-Means Clustering classification process produces two clusters which can be used as a reference for retailers that are selling well and not selling well. The system that has been created is good because the K value used, namely K = 2, has the largest decrease in SSE, namely SSE = 30,426 x 10¹⁶.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 07 Aug 2024 06:52 |
| Last Modified: | 07 Aug 2024 06:52 |
| URI: | http://eprints.uty.ac.id/id/eprint/15878 |
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