Application of Data Mining to Predict Sales of the Best-Selling Dolls at Chudalla Store Using the K-Nearest Neighbor (K-NN) Method
Abstract
Sales are important for the success of a shop to survive amidst business competition. Chudalla Store continues to innovate to increase doll sales every day. So that the dolls sold experience continuous change of goods. So that the stock of dolls does not pile up and cause losses to the shop owner. Data mining is a data collection technique that is suitable for use in business, especially for predicting sales of goods. There are several methods in data mining, one of which is the K-Nearest Neighbor (K-NN) method which is suitable for use as a method for predicting sales of the best-selling dolls at the Chudalla Store. The K-Nearest Neighbor (K-NN) method is a method in data mining that is often used to classify new objects and is also often used as a predictive value for solving problems in the business industry. The K-Nearest Neighbor (K-NN) method helps in predicting the best selling dolls at Chudalla Store.
Full Text:
PDFReferences
A. U. Haspriyanti and P. W. Prasetyaningrum, "Penerapan Data Mining Untuk Prediksi Layanan Produk," JURNAL INFORMATION SYSTEM & ARTIFICIAL INTELLIGENCE, vol. Volume 1, pp. 100-107, 2021.
Rismala, I. Ali and A. R. Rinaldi, "PENERAPAN METODE K-NEAREST NEIGHBOR UNTUK PREDIKSI," JATI (Jurnal Mahasiswa Teknik Informatika), vol. Volume.7 No.1, pp. 585-590, 2023.
C. Anisa and Andri, "PENERAPAN ALGORITMA K-NEAREST NEIGHBOR UNTUK," Bina Darma Conference on Computer Science, pp. 199-208, 2020.
S. P. Dewi, Nurwati and E. Rahayu, "Penerapan Data MiningUntuk Prediksi Penjualan Produk Terlaris Menggunakan Metode K-Nearest Neighbor," Building of Informatics, Technology and Science (BITS) , vol. Volume.3 Nomor.4, p. 639−648, 2022.
I. Yolanda and H. Fahmi, "Penerapan Data Mining Untuk Prediksi Penjualan Produk," JIKOMSI [Jurnal Ilmu Komputer dan Sistem Informasi] , vol. Volume.3 Nomor.3, pp. 9-15, 2021.
A. Pratama, B. S. Ginting and Nurhayati, "PENERAPAN DATA MINING UNTUK PREDIKSI MEREK," Jurnal Pancabudi, vol. 14 No.2, pp. 54-64, 2021.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.