CLUSTERING OF CLOTHING SALES DATA AT TOP STORE USING K-MEANS METHOD
DOI:
10.33395/sinkron.v7i2.11244Keywords:
Data Mining, K-means , RapidminerAbstract
In the era of globalization, the development of technological sophistication is growing rapidly which is an aspect that can be utilized to achieve convenience, especially in the flow of information. This technological sophistication by all accounts is increasingly spreading with the use of computers which are currently very popular in various areas of life. For example in the fields of education, entertainment, health, especially in the business sector. Top Store is a store that is engaged in selling clothes, however, of the various types of clothes that are sold, of course, not all of them are selling very well, and some are not selling well. Sales data, purchase of goods and unexpected expenses at Top Shop is not structured, so the data are only serves as an archive for the store and not be utilized for the development strategy of marketing. Therefore, it is necessary to apply Clustering of Clothing Sales Data in Top Stores with the K- Means Method . The K-means method can be applied to Top Stores to determine which clothes are selling very well, selling well and not selling well. The application of the K-Means method in Top Stores, namely by grouping clothing stock data. Then choose 3 clusters randomly as the initial centroid. After the data in each cluster does not change, it can be seen that the final result is that there are 21 best-selling articles, 17 articles that are selling well and 12 articles that are not selling well. Then applying the K-means method to Rapidminer is done by entering product stock data, namely initial stock, sold stock and final stock which will become a database on Ms. Excel, the data is then connected to the Rapidminer Tools , and will be processed and formed K-means.
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References
Aji, A. M. B. (2017). Pengelompokan Peminatan Outline Tugas Akhir Dengan Menggunakan Algoritma K-Means Pada AMIK MI BSI Jakarta. 5(2), 1–9.
Aulia, S. (2021). Klasterisasi Pola Penjualan Pestisida Menggunakan Metode K-Means Clustering (Studi Kasus Di Toko Juanda Tani Kecamatan Hutabayu Raja). Djtechno: Jurnal Teknologi Informasi, 1(1), 1–5. https://doi.org/10.46576/djtechno.v1i1.964
Bahar, A., Pramono, B., & Sagala, L. H. S. (2016). Penentuan strategi penjualan alat-alat tattoo di studio sonyxtattoo menggunakan metode. SemanTIK, 2(2), 75–86.
Bastian, A., Sujadi, H., & Febrianto, G. (n.d.). Penerapan Algoritma K-Means Clustering Analysis Pada Penyakit Menular Manusia (Studi Kasus Kabupaten Majalengka). 1, 26–32.
Gustientiedina, G., Adiya, M. H., & Desnelita, Y. (2019). Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan. Jurnal Nasional Teknologi Dan Sistem Informasi, 5(1), 17–24. https://doi.org/10.25077/teknosi.v5i1.2019.17-24
Handoko, S., Fauziah, F., & Handayani, E. T. E. (2020). Implementasi Data Mining Untuk Menentukan Tingkat Penjualan Paket Data Telkomsel Menggunakan Metode K-Means Clustering. Jurnal Ilmiah Teknologi Dan Rekayasa, 25(1), 76–88. https://doi.org/10.35760/tr.2020.v25i1.2677
Hasugian, P. S. (2018). Penerapan Data Mining untuk Klasifikasi Produk Menggunakan Algoritma K- Means (Studi Kasus : Toko Usaha Maju Barabai). Jurnal Mantik Penusa, 2(2), 191–198.
Indriyani, F., & Irfiani, E. (2019). Clustering Data Penjualan pada Toko Perlengkapan Outdoor Menggunakan Metode K-Means. JUITA : Jurnal Informatika, 7(2), 109. https://doi.org/10.30595/juita.v7i2.5529
Issn, I. P. E.-. (2018). Analisis Clustering Menggunakan Algoritma K-Means Terhadap Penjualan Produk Padapt Batamas Niaga Jaya. Computer Based Information System Journal, 02, 20–35.
Mardalius, M. (2018). Pemanfaatan Rapid Miner Studio 8.2 Untuk Pengelompokan Data Penjualan Aksesoris Menggunakan Algoritma K-Means. Jurteksi, 4(2), 123–132. https://doi.org/10.33330/jurteksi.v4i2.36
MURTI, M. A. W. K. (2017). Penerapan Metode K-Means Clustering Untuk Mengelompokan Potensi Produksi Buah – Buahan Di Provinsi Daerah Istimewa Yogyakarta. Skripsi.
NOVIANTO, R. (2019). Penerapan Data Mining menggunakan Algoritma K-Means Clustering untuk Menganalisa Bisnis Perusahaan Asuransi. JATISI (Jurnal Teknik Informatika Dan Sistem Informasi), 6(1), 85–95. https://doi.org/10.35957/jatisi.v6i1.150
Rahmat C.T.I., B., Agidtama Gafar, A., Fajriani, N., Ramdani, U., Rihin Uyun, F., Purnamasari P., Y., & Ransi, N. (2017). Implemetasi k-means clustering pada rapidminer untuk analisis daerah rawan kecelakaan. Seminar Nasional Riset Kuantitatif Terapan 2017, April, 58–60.
Rianti, E. (2017). Data Mining Dalam Menentukan Penjualan Laris Menggunakan Metode Clustering.
KomTekInfo, 4(2), 267–283.
Yulianti, Y., Utami, D. Y., Hikmah, N., & Hasan, F. N. (2019). Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Mengetahui Minat Customer Di Toko Hijab. Jurnal Pilar Nusa Mandiri, 15(2), 241–246. https://doi.org/10.33480/pilar.v15i2.650
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