ANALISIS PERBANDINGAN ALGORITMA NAIVE BAYES, J48,DAN RANDOM FOREST TREE DALAM PENINGKATAN LOYALITAS PELANGGAN UMKM DENGAN VOUCHER BELANJA

  • Maya Cendana Program Studi Teknok Informatika, Universitas Trilogi
  • Silvester Dian Handy Permana Program Studi Teknok Informatika, Universitas Trilogi
Keywords: Comparation Analysis, Algorithm Comparation, Naive Bayes, J48, Random Forest Tree

Abstract

Information technology has been used for a long time for MSME businesses. Many people who have MSME businesses use online stores to promote their businesses. To be able to attract old customers to shop back to the online store, one of them is by giving a shopping voucher. Shopping vouchers are given to existing customers who have the potential to shop back to online stores. In determining which customer is the right data mining algorithm is needed to find the right information where the customer can shop again. But the error of choosing an algorithm can result in not being optimal in the projected income. In this study, we will analyze and compare the Naive Bayes, J48, and Random Forest Tree algorithms for case studies of online stores. This study involved 7 criteria that would be used to become material in data processing. From the results of this study, a random forest tree is the best algorithm to determine the potential of online store customers. The results of this study are used to help the decision-making process of giving shopping vouchers to customers so that MSME businesses can run and get optimal profits

 

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References

[1] Fikri, A. (2013). Penerapan Data Mining Untuk Mengetahui Tingkat Kekuatan Beton Yang Dihasilkan Dengan Metode Estimasi Menggunakan Linear Regression. Fakultas Ilmu Komputer UDINUS, 1–12.
[2] Gerber, G., Faou, Y. Le, Lopez, O., Trupin, M., Gerber, G., Faou, Y. Le, … Trupin, M. (2018). The impact of churn on client value in health insurance , evaluation using a random forest under random censoring To cite this version : HAL Id : hal-01807623 The impact of churn on client value in health insurance , evaluation using a random forest under.
[3] Ghofar, M. A., & Kurniawan, Y. I. (2018). Aplikasi Pengelompokan Pelanggan Pada Ums Store Menggunakan Algoritma K-Means. Jurnal Teknologi & Manajemen Informatika –, 4(1).
[4] Gunadi, G., & Sensuse, D. I. (2012). Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Buku Dengan Menggunakan Algoritma Apriori Dan Frequent Pattern Growth ( Fp-Growth ) : Telematika, 4(1), 118–132.
[5] Hartanto, B. C., Palit, H. N., Studi, P., Informatika, T., Industri, F. T., Petra, U. K., & Siwalankerto, J. (2017). Perancangan dan Pembuatan Website E-Commerce untuk UMKM yang dibina oleh Universitas Kristen Petra, 1–6.
[6] Hong, H., Liu, J., Bui, D. T., Pradhan, B., Acharya, T. D., Pham, B. T., … Ahmad, B. Bin. (2018). Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China). Catena, 163(January), 399–413. https://doi.org/10.1016/j.catena.2018.01.005
[7] Mediana Aryuni. (2016). TAHAP-TAHAP DATA MINING.
[8] Permana, S. D. H. (2016). E-marketing strategy in game industry with social media using e-business model, 258–263.
Published
2019-10-17