BERNESSA, VALENCIA (2020) Analisa Penjualan Di Alenxi Technology Menggunakan Algoritma Apriori. Undergraduate thesis, Universitas Stikubank.
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Abstract
Alenxi Technology Semarang merupakan distributor sparepart mesin pabrik yang memanfaatkan layanan e-commerce sebagai pemasarannya. Produk yang dijual memiliki berbagai macam kategori produk, sehingga memerlukan data mining untuk mendapatkan informasi berupa pengetahuan yang sampai saat ini belum diketahui secara manual dari sebuah kumpulan data. Tujuan penelitian ini untuk mendapatkan suatu itemset yang terjual secara bersamaan dalam satu transaksi dengan teknik association rules dan algoritma apriori yang dijadikan sebagai pembuat kandidat kombinasi item yang berdasar pada aturan tertentu yang kemudian diuji apakah kombinasi item tersebut telah mencapai syarat minimum support yang kemudian digunakan untuk membuat aturan-aturan yang memenuhi syarat minimum confidence. Penelitian ini memanfaatkan aplikasi R-Studio untuk menganalisa data. Hasil penelitian ini adalah mendapatkan pola penjualan dengan algoritma apriori yaitu association rules penjualan 1 itemset dengan minimum support 0.13 dan minimum confidence 0.3 membentuk 7 rules. Sedangkan association rules penjualan 2 itemset dengan minimum support 0.08 dan minimum confidence 0.6 membentuk 5 rules. Association rules penjualan 3 itemset dengan minimum support 0.04 dan confidence 0.8 membentuk 5 rules. Hasil association rules ini dapat memberikan rekomendasi kepada pihak Alenxi Technology untuk mengatur tata letak tampilan produk pada website www.alenxi.com. Alenxi Technology Semarang is a distributor of factory machinery spare parts applying e-commerce services as its marketing. The selling products have a variety of categories and thereby requires data mining to obtain information in the form of knowledge which so far has not been identified manually from a data set. The aim of the research is to obtain an itemset thatvi was sold simultaneously in one transaction using association rules technique and apriori algorithm. It was prepared as a candidate maker for the combination of items based on certain rules and tested whether the combination of these items had reached the minimum support requirement. Subsequently, it was used to make rules which meet the minimum confidence requirements. The data analysis was carried out using R-Studio. The results of the research obtain selling patterns with apriori algorithm, namely association rules for selling 1 itemset is with a minimum support of 0.13 and minimum confidence of 0.3 forming 7 rules. While the association rules for selling 2 itemset is with a minimum support of 0.08 and a minimum of confidence of 0.6 forming 5 rules. Besides, association rules selling 3 itemset is with a minimum support of 0.04 and confidence 0.8 forming 5 rules. The evidence from this research implies recommendations to Alenxi Technology to organize the layout of product displays on the website www.alenxi.com. K
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | NIM.16.01.53.0022 SKR.I.05.01.1879 |
| Uncontrolled Keywords: | Alenxi Technology, Data Mining, Association Rules, Algoritma Apriori, Pola Penjualan Alenxi Technology, Data Mining, Association Rules, Apriori Algorithm, Selling Patterns |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Faculty / Institution: | Fakultas Teknologi Informasi > Program Studi Teknik Informatika |
| Depositing User: | H Hayati |
| Date Deposited: | 09 Sep 2020 05:24 |
| Last Modified: | 09 Sep 2020 05:24 |
| URI: | https://eprints.unisbank.ac.id/id/eprint/7043 |
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