Implementasi Data Mining Penjualan Produk Kosmetik Pada PT. Natural Nusantara Menggunakan Algoritma Apriori

Fajar Adhinda Kusuma Wardani, Titin Kristiana

Abstract


Women's life can not be separated from cosmetics. In addition to beautifying themselves, cosmetics are also used for health purposes. Cosmetics are basically one of the basic needs of women. Every day the sales transaction data at PT. Natural Nusantara is increasing and causing huge data storage. Most sales transaction data is only used as archives without being used properly. The data should be used to see the relevance of each item purchased by consumers simultaneously. This research analyzes data using a priori algorithm method, with this method it is known that cosmetic products purchased simultaneously and most sold by looking at the value of support and confidence. In the process of data processing using manual calculation and RapidMiner 5.3 software to analyze datasets at PT. Natural Nusantara. The results of this study use 10% support and 50% confidence. This study produced 7 rules for association rules.


Keywords


Cosmetic Products, Sales, Apriori Algorithm, Association Rule

References


Kusrini, & Taufiq, L. E. (2009). ALGORITMA DATA MINING. Yogyakarta.

Masnur, A. (2015). Analisa Data Mining Menggunakan Market Basket Analysis untuk Mengetahui Pola Beli Konsumen. SATIN-Sains Dan Teknologi Informasi, 1(2), 32–40.

Purnia, D. S., & Warnilah, A. I. (2017). Implementasi Data Mining Pada Penjualan Kacamata Menggunakan Algoritma Apriori. IJCIT (Indonesian Journal ON COmputr and Information Technologi), 2(2), 31–39. Retrieved from http://ejournal.bsi.ac.id/ejurnal/index.php/ijcit/article/view/2776

Adha, N., Sianturi, L. T., & Siagian, E. R. (2017). Implementasi Data Mining Penjualan Sabun Dengan Menggunakan Metode Apriori ( Studi Kasus : PT. Unilever). Majalah Ilmiah INTI, 12(2), 219–223.

Afdal, M., & Rosadi, M. (2019). Penerapan Association Rule Mining Untuk Analisis. 5(1), 99–108.

Evadin, S., Nazir, A., Yusra, & Pizaini. (2017). Analisa Faktor Yang Mempengaruhi Kondisi Kesehatan Menggunakan Algoritma Frequent

Pattern Growth. 1(1), 1–6.

Informasi, J. T., Studi, P., Informatika, T., & Malang, P. N. (2017). Ridwan Rismanto 1 , Lucki Darmawan 2 , Arief Prasetyo 3. 04(02), 83–88.

Informatika, P. M. (n.d.). Keterkaitan Data Untuk Analisa Keranjang.

Junaidi, A. (2019). Implementasi Algoritma Apriori dan FP-Growth Untuk Menentukan Persediaan Barang. 08, 61–67.

Kanti, S., & Indrajit, R. E. (2017). Implementasi Data Mining Penjualan Handphone Oppo Store Sdc Tanggerang Dengan Algoritma Appriori. (November), 1–2.

Muflikhah, L., Ratnawati, D. E., & Putri, R. R. M. (2018). DATA MINING. Malang.

Nofriansyah, D., & Nurcahyo, G. W. (2015). Algoritma Data Mining dan Pengujian. Yogyakarta.




DOI: https://doi.org/10.31294/p.v22i1.6520

ISSN2579-3500

Dipublikasikan oleh LPPM Universitas Bina Sarana Informatika

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Kota Jakarta Pusat, DKI Jakarta 10450
Telepon: 021-21231170, ext. 704 / 705
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License