Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan
| Main Authors: | Riszky, Ariefana Ria, Sadikin, Mujiono |
|---|---|
| Other Authors: | Universitas Mercubuana |
| Format: | Article info application/pdf eJournal |
| Bahasa: | ind |
| Terbitan: |
Departemen Teknik Komputer, Fakultas Teknik, Universitas Diponegoro
, 2019
|
| Subjects: | |
| Online Access: |
https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13234 https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13234/12516 https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/downloadSuppFile/13234/272 |
Daftar Isi:
- Pelaksanaan strategi pemasaran memerlukan acuan agar promosi dapat tepat sasaran, misalnya dengan mencari hubungan kesamaan antar item produk. Penelitian ini mengkaji penerapan metode association rule dan algoritma apriori pada dataset transaksi pembelian untuk membantu membentuk kandidat kombinasi antar item produk dalam promosi rekomendasi produk bagi pelanggan. Dataset transaksi pembelian dikumpulkan pada bulan Oktober dan November 2018 sejumlah 1027 data. Pada eksperimen, ditentukan nilai support minimum 85% dan nilai confidence minimum 90% dengan pengolahan data menggunakan software Weka versi 3.9. Algoritma apriori dapat menghasilkan aturan asosiasi sebagai acuan dalam promosi produk dan pendukung keputusan dalam memberikan rekomendasi produk kepada konsumen berdasarkan nilai support dan confidence minimum yang telah ditetapkan.
- The implementation of a marketing strategy requires a reference so that promotion can be on target, such as by looking for similarities between product items. This study examines the application of the association rule method and apriori algorithm to the purchase transaction dataset to assist in forming candidate combinations among product items for customer recommended product promotion. The purchase transaction dataset was collected in October and November 2018 with a total data of 1027. In the experiment, the minimum value of support is 85%, and the minimum confidence value is 90% by processing data using the Weka software 3.9 version. Apriori algorithm can form association rules as a reference in the promotion of company products and decision support in providing product recommendations to customers based on defined minimum support and confidence values.