Rancang Bangun Aplikasi Data Mining pada Penjualan Distro Bloods Berbasis Web menggunakan Algoritma Apriori
Article Sidebar
Main Article Content
Abstract
The design of this data mining application is a computerized system in the field of technology, this proves that technological developments in data processing are increasingly advanced, this can be the basis for the development of data processing systems for sales of bloods based web applications using a priori algorithms, problems in this bloods distribution cannot Minimizing the decline in sales at the Jakarta clothing event in 2019, it is necessary to evaluate the sales data, with market basket analysis or consumer shopping baskets to find out consumer shopping patterns as a reference for the sale strategy of event Jakarta clothing at the end of the year. This analysis uses a priori algorithm with the association rule method, while the SDLC (Software Development Life Cycle) method is used as the basis for developing expert systems. From the results of the study, it was found that sales data for 5 days and 7 items got the highest 100% confidence value from the itemset calculation 1,2,3 which passed the selection so that they became aware of consumer purchasing patterns and rearranged product layouts for promotion and improving the correct sales strategy.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to JTIK journal and Research Division, KITA Institute as the publisher of the journal. Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
JTIK journal and Research Division, KITA Institute and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in JTIK journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form JTIK]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Muhammad Wali (Editor-in-Chief)
Editorial Office of Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Research Division, KITA Institute
Teuku Nyak Arief Street Nomor : 7b, Lamnyong, Lamgugop, Kota Banda Aceh
Telp./Fax: 0651-8070141
Email: jtik@lembagakita.org - journal@lembagakita.org
References
Tampubolon, K., Saragih, H., Reza, B., Epicentrum, K. and Asosiasi, A., 2013. Implementasi Data Mining Algoritma Apriori pada sistem persediaan alat-alat kesehatan. Majalah Ilmiah Informasi dan Teknologi Ilmiah, 1(1), pp.93-106.
Wijayanti, A., 2017. Analisis Hasil Implementasi Data Mining Menggunakan Algoritma Apriori Pada Apotek. Jurnal Edukasi dan Penelitian Informatika (JEPIN).
Jayadi, J. and Patombongi, A., 2017. Implementasi Aplikasi Data Mining Pada Apotek Kimia Farma Bahteramas Menggunakan Algoritma Apriori. Simtek: Jurnal Sistem Informasi dan Teknik Komputer, 2(1), pp.87-95.
Dewantara, H., Santosa, P.B. and Setyanto, N.W., 2013. Perancangan Aplikasi Data Mining dengan Algoritma Apriori Untuk Frekuensi Analisis Keranjang Belanja pada Data Transaksi Penjualan (Studi Kasus di Swalayan KPRI Universitas Brawijaya). Jurnal Rekayasa dan Manajemen Sistem Industri, 1(3), pp. 415-426.
Packianather, M.S., Davies, A., Harraden, S., Soman, S. and White, J., 2017. Data mining techniques applied to a manufacturing SME. Procedia CIRP, 62, pp.123-128.
Luthfi, K. and Taufiq, E., 2009. Algoritma Data Mining. Yogyakarta: Andi.
Listriani, D., Setyaningrum, A.H. and Eka, F., 2016. Penerapan Metode Asosiasi Menggunakan Algoritma Apriori Pada Aplikasi Analisa Pola Belanja Konsumen (Studi Kasus Toko Buku Gramedia Bintaro). Jurnal Teknik Informatika, 9(2).
Sinha, G. and Ghosh, S.M., 2014. Identification of best algorithm in association rule mining based on performance. Int. J. Comput. Sci. Mob. Comput, 3(11), pp.38-45.
Masih, S. and Tanwani, S., 2014. Data mining techniques in parallel and distributed environment-a comprehensive survey. Technology, 4(2), pp.1432-1436.
Faisal, F., 2018. Penerapan Metode Association Rule Mining Untuk Analisis Dan Implementasi Teknik Data Mining Dalam Memprediksi Strategi Pemasaran Produk Unilever. Jurnal INSTEK (Informatika Sains dan Teknologi), 3(1), pp.151-160.
Tan, P.N., Steinbach, M. and Kumar, V., 2016. Introduction to data mining. Pearson Education India.
Han, J. and Kamber, K., 2006. The Apriori Algorithm: Finding Frequent Itemsets Using Candidate Generation. Data Mining. Concepts and Techniques.