Penerapan Algoritma K-Means Clustering untuk Menganalisis Penjualan pada Toko Ayu Collection Barbasis Web
DOI:
https://doi.org/10.32493/informatika.v6i3.12380Keywords:
Sales Analysis, K-Means Clustering, Website, Data MiningAbstract
The main activity in business is to determine the amount of stock that must be maintained to analyze the profit of each item sold. Therefore, groups such as high and low sales categories are needed to consider the stock of goods in the sales process. Ayu Collection store is a store that sells various types of clothing and accessories that have not implemented the grouping of goods in its sales information system to provide the maximum and the minimum number of stock items to be sold at the store. The process of grouping goods is still done manually, which is based on observations from shop owners. Therefore, to maintain the stock of goods so that no items are empty, this study aims to support the process of determining the stock of goods by building a model that can group items into high and low categories in sales using k-means clustering. The group with the highest centroid will be the group with the highest selling rate, while the lowest centroid will be the group with the least demand in sales. The data used in this study was taken from sales data in 2017 and 2018. The clustering scenario uses the variable name of goods, data of incoming goods, data of goods out, and stock of goods. The results of this study are showing the value of system performance in grouping goods by 83.33%.References
Devi, C., Soleman, O., Pramaita, N., & Sudarma, M. (2020). Classification Of Loyality Customer Using K-Means Clustering , Studi Case : PT . Sucofindo ( Persero ). 5(2).
Dr. Sandu Siyoto, SKM, M.Kes, M. Ali Sodik, M. (2015). Buku Metode Penelitian Kualitatif dan Kuantitatif.
Dwitri, N., Tampubolon, J. A., Prayoga, S., Zer, F. I. R. ., & Hartama, D. (2020). Penerapan Algoritma K-Means Dalam Menentukan Tingkat Penyebaran Pandemi Covid-19 Di Indonesia. JurTI (Jurnal Teknologi Informasi), 4(1), 128–132. Retrieved from http://jurnal.una.ac.id/index.php/jurti/article/view/1266
Hasanah, H. (2017). TEKNIK-TEKNIK OBSERVASI (Sebuah Alternatif Metode Pengumpulan Data Kualitatif Ilmu-ilmu Sosial). At-Taqaddum, 8(1), 21. https://doi.org/10.21580/at.v8i1.1163
Hastanti, R. P. (2011). Analisis Dan Perancangan Sistem Penjualan Berbasis Web ( E-Commerce ). 1–8.
Hernandhi, D. T., Astuti, E. S., & Priambada, S. (2018). Desain Sistem Informasi Pemasaran Berbasis Website Untuk Promosi ( Studi Kasus pada Kedai Ayam Geprak & Sambal Bawang Malang ). Jurnal Administrasi Bisnis, 55(1), 1–10.
Mirzaqon, A. T., & Purwoko, B. (2017). Studi Kepustakaan Mengenai Landasan Teori Dan Praktik Konseling Expressive Writing Library. Jurnal BK UNESA, 1–8.
Nawang, M., Kurniawati, L., Duta, D., Akuntansi, K., Informasi, S., & Akuntansi, K. (2017). Rancang Bangun Sistem Informasi Pengolahan Data Persediaan Barang Berbasis Dekstop Dengan Model. 13(2), 233–238.
Oktarina, C., Notodiputro, K. A., & Indahwati, I. (2020). Comparison of K-Means Clustering Method and K-Medoids on Twitter Data. Indonesian Journal of Statistics and Its Applications, 4(1), 189–202. https://doi.org/10.29244/ijsa.v4i1.599
Siregar, M. H. (2018). Data Mining Klasterisasi Penjualan Alat-Alat Bangunan Menggunakan Metode K-Means (Studi Kasus Di Toko Adi Bangunan). Jurnal Teknologi Dan Open Source, 1(2), 83–91. https://doi.org/10.36378/jtos.v1i2.24
Supardi, R., & Kanedi, I. (2020). Implementasi Metode Algoritma K-Means Clustering pada Toko Eidelweis. JurTI (Jurnal Teknologi Informasi), 4(2), 270–277. Retrieved from http://jurnal.una.ac.id/index.php/jurti/article/view/1444
Sutejo, B. S. (2006). Internet Marketing : Konsep Dan. Jurnal Manajemen, 6(1), 41–57.
Taufani, M., Riyadi, R., & Dewantara, R. (2016). Analisis Dan Desain Sistem Informasi Pemasaran (Studi pada Sistem Informasi Pemasaran untuk Promosi CV. Intan Catering). Jurnal Administrasi Bisnis S1 Universitas Brawijaya, 38(2), 1–10.
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