Yudiansyah, Yudiansyah and Anggraeni, Irma and Denih, Asep (2024) Sistem Rekomendasi Menu Makanan dan Minuman dengan Metode K- MEANS dan FP-GROWTH. Skripsi thesis, Universitas Pakuan.
![[img]](http://eprints.unpak.ac.id/style/images/fileicons/text.png) |
Text
LAPORAN SIDANG SKRIPSI - 065117089 - Yudiansyah.pdf Download (1MB) |
|
Text
HALAMAN PENGESAHAN (1).pdf Download (84kB) |
Abstract
Sistem Rekomendasi Menu Makanan dan Minuman dengan Metode K- MEANS dan FP-GROWTH pada Cafe Milarian Asep Denih1) , Irma Anggraeni 2) , Yudiansyah3) 1,2,3 Program Studi Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan 1,2,3 Jl. Pakuan No.1, Ciheuleut, Bogor, 16143 Email: 1asep.denih@unpak.ac.id, 2 irma.anggraeni@unpak.ac.id, 3 yudiansyah04@gmail.com Research aims to enhance operational efficiency and customer experience in a cafe through the implementation of data mining-based technology. The two main methods used in this study are K-Means Clustering and the FP-Growth Algorithm. K-Means is employed to group customers based on their menu preferences and purchasing behavior, while FP-Growth is used to analyze frequently occurring purchase patterns. The implementation of K-Means enables the cafe to devise more targeted marketing strategies, adjusting menus and promotions to meet customer needs. Additionally, FP�Growth aids in identifying relationships between frequently co-purchased menu items, allowing the cafe to create more enticing bundled offers and boost cross-menu sales. The implementation of this technology is expected to have a positive impact on customer satisfaction, increase sales, and optimize inventory management in the cafe. By combining these two methods, cafes can improve operational efficiency, provide a better customer experience, and compete effectively in the increasingly competitive cafe industry. Keyword : Caffe Technology Efficiency, K-Means, FP-Growth, Product Recommendation
| Item Type: | Thesis (Skripsi) |
|---|---|
| Subjects: | Fakultas Ilmu Pengetahuan Alam dan Matematika > Ilmu Komputer |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam > Ilmu Komputer |
| Depositing User: | PERPUSTAKAAN FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM UNPAK |
| Date Deposited: | 29 Aug 2024 07:40 |
| Last Modified: | 29 Aug 2024 07:40 |
| URI: | http://eprints.unpak.ac.id/id/eprint/8103 |
Actions (login required)
 |
View Item |