Implementation of Association Rules to Manage Cross-Selling and Up-Selling for IT Shop
Abstract
Nowadays sales marketing strategies in showrooms are increasingly innovative. Utilizing information technology, especially data mining to obtain customer habits in shopping. Customer's shopping habits are recorded in each transaction and stored in a data warehouse. This transaction data is actually very valuable and can be elaborated to be used to manage cross selling and up selling in sales stores, including IT showroom stores. IT Showroom stores usually have unusual or unexpected customers shopping for IT needs. Therefore this potential can be exploited for analysis to get behavior from customers by analyzing transactions in a certain period of time using the Rapidminer application. Rapidminer is a fit application to solve this problem because it is equipped with various algorithms, one of which is association rules. Association rules are algorithms that can be used to analyze data and produce recommendations for cross selling and up selling.
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References
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[2] R. Sarkar, “Online Shopping vs Offline Shopping : A Comparative Study,” Int. J. Sci. Res. Sci. Technol., vol. 3, no. 1, pp. 424–431, Jan. 2017.
[3] J. S. Johnson and S. B. Friend, “Contingent cross-selling and up-selling relationships with performance and job satisfaction: an MOA-theoretic examination,” J. Pers. Sell. Sales Manag., vol. 35, no. 1, pp. 51–71, Jan. 2015.
[4] P. Surya Sumartha, F. Samopa, P. S. Sumartha, and F. Samopa, “Cross Selling Product Bundling Based on Customer Satisfaction Study Case Meat,” Int. J. Educ. Res., vol. 5, no. 1, pp. 241–252, 2017.
[5] E. Miranda and N. Elfreida, “Data Warehouse, Data Mining Dan Konsep Cross-Selling Pada Analisis Penjualan Produk,” ComTech Comput. Math. Eng. Appl., vol. 1, no. 2, p. 344, 2010.
[6] M. P. A. Ariawan, P. B. I. S. Putra, and I. M. Sudarma, “Analysis of Enterprise Architecture Design Using TOGAF Framework : A Case Study at Archival Unit of Faculty of Agricultural Technology of,” vol. 2, no. 2, pp. 52–57, 2017.
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[9] D. Ardiada, P. A. Ariawan, and M. Sudarma, “Evaluation of Supporting Work Quality Using K-Means Algorithm,” Int. J. Eng. Emerg. Technol., vol. 3, no. 1, pp. 52–55, 2018.
[10] K. A. Shobirin, A. P. S. Iskandar, and I. B. A. Swamardika, “Data Warehouse Schemas using Multidimensional Data Model for Retail,” Int. J. Eng. Emerg. Technol., vol. 2, no. 1, p. 84, 2017.
[11] I. G. W. Darma, K. S. Utami, N. Wayan, and S. Aryani, “Data Warehouse Analysis to Support UMKM Decisions using the Nine-step Kimball Method,” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, pp. 1–4, 2019.
[12] I. N. A. Prabawa, D. Agung, K. Arimbawa, and I. G. N. Janardana, “Analysis and Design Data Warehouse For E-Travel Business Optimization,” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, 2019.
[13] P. Novenando, M. Weking, I. G. Ngurah, W. Partha, and A. I. Weking, “Application of Data Mining with Support Vector Machine ( SVM ) in Selling Prediction Trend of Spiritual Goods ( Case Study : PT . X Bali ),” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, pp. 20–24, 2019.
[14] R. W. Sari, A. Wanto, and A. P. Windarto, “Implementasi Rapidminer Dengan Metode K-Means (Study Kasus: Imunisasi Campak Pada Balita Berdasarkan Provinsi),” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 2, no. 1, pp. 224–230, 2018.
[15] M. Mardalius, “Pemanfaatan Rapid Miner Studio 8.2 Untuk Pengelompokan Data Penjualan Aksesoris Menggunakan Algoritma K-Means,” Jurteksi, vol. 4, no. 2, pp. 123–132, 2018.
[16] I. W. S. Pramana, P. R. Iswardani, N. Wayan, and S. Aryani, “Application of Data Mining in Optimization of Hotel ’ s Food and Beverage Costs,” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, pp. 3–7, 2019.
[17] S. I. Murpratiwi, A. A. N. Narendra, and M. Sudarma, “Mapping Patterns Achievement Based on CRISP-DM and Self Organizing Maps (SOM) Methods,” Int. J. Eng. Emerg. Technol., vol. 2, no. 1, pp. 1–6, 2017.
[18] K. S. Utami, I. G. W. Darma, N. Wayan, and S. Aryani, “Stock management using K-means method and Time Series method as Stock Order,” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, pp. 60–64, 2019.
[19] A. P. S. Iskandar, K. A. Shobirin, and K. Oka Saputra, “Analysis of Shopping Cart At Drugs Store By Using An Apriori Algorithm,” Int. J. Eng. Emerg. Technol., vol. 2, no. 1, p. 97, 2017.
[20] W. Wahyudin, I. P. A. Wijaya, and I. B. A. Swamardika, “Data Mining for Clustering Revenue Plan Expense Area (APBD) by using K-Means Algorithm,” Int. J. Eng. Emerg. Technol., vol. 2, no. 1, p. 87, 2017.
[21] D. Agung, K. Arimbawa, I. N. A. Prabawa, and P. A. Mertasana, “Implementation of Apriori Algorithm in Determining Tourism Visit Patterns to Bali,” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, pp. 10–14, 2019.
[22] Y. D. Lestari, “Penerapan Data Mining Menggunakan Algoritma Fp-Tree Dan Fp-Growth Pada Data Transaksi Penjualan Obat,” in Seminar Nasional Teknologi Informasi dan Komunikasi ( SNASTIKOM 2015 ), 2015, no. Snastikom, pp. 60–65.
[23] A. Ikhwan, D. Nofriansyah, and Sriani, “Penerapan Data Mining dengan Algoritma Fp-Growth untuk Mendukung Strategi Promosi Pendidikan ( Studi Kasus Kampus STMIK Triguna Dharma ),” Saintikom, vol. 14, no. 3, pp. 211–226, 2015.
[24] S. Wahyuni, K. S. S. Mochammad, and I. Perangin-Angin, “Implementasi Rapidminer dalam Menganalisa Data Mahasiswa Drop Out,” J. Abdi Ilmu, vol. 10, no. 2, pp. 2013–2016, 2017.
[25] A. Agung, G. Oka, K. Adnyana, and K. O. Saputra, “Design of Data Warehouse for University Library using Kimball and Ross 9 Steps Methodology,” Int. J. Eng. Emerg. Technol., vol. 4, no. 1, 2019.
Published
2020-08-24
How to Cite
ANDIS INDRAWAN, I Wayan; OKA SAPUTRA, Komang; LINAWATI, Linawati.
Implementation of Association Rules to Manage Cross-Selling and Up-Selling for IT Shop.
International Journal of Engineering and Emerging Technology, [S.l.], v. 4, n. 2, p. 60--63, aug. 2020.
ISSN 2579-5988.
Available at: <https://ojs.unud.ac.id/index.php/ijeet/article/view/59973>. Date accessed: 21 nov. 2024.
doi: https://doi.org/10.24843/IJEET.2019.v04.i02.p11.
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