Amrullah, Azam Gita (2026) Analisis Algoritma Apriori Untuk Rekomendasi Paket Bundling Penjualan Barang Pada Toko Retail Sinar Rejeki. Undergraduate thesis, Universitas Hayam Wuruk Perbanas.
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Abstract
Sinar Rejeki Store is a retail business that still determines product promotions and bundling packages manually based on the owner's intuition, without utilizing actual sales transaction data. This approach risks producing product combinations that do not reflect real customer purchasing patterns. Therefore, this study aims to analyze sales transaction data using the Apriori algorithm to generate product bundling recommendations for the snack and beverage categories. Data collection was conducted through observation, interviews, and literature studies. The analysis process includes data selection, data cleaning, data transformation into a binary matrix, and the application of the Apriori algorithm using the Pandas and MLxtend libraries on Google Colab. The results show that a minimum support value of 0.01 and a minimum confidence value of 0.20 produced the most representative association rules, identifying four product pairs that are consistently purchased together: Beng-Beng with Ultra Milk Coklat, Aqua 600Ml with Roma Malkist, Tango Wafer with Good Day Cappuccino, and Chitato with Teh Botol Sosro, each with a lift ratio above 2. These findings were translated into four concrete bundling package recommendations that can serve as an objective basis for Sinar Rejeki Store in designing data-driven promotional strategies.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Subjects: | 000 - COMPUTER SCIENCE, INFORMATION, GENERAL WORKS > 000 - 009 COMPUTER SCIENCE, INFORMATION, GENERAL WORKS > 005 - COMPUTER PROGRAMMING, PROGRAMS & DATA |
| Divisions: | Bachelor of Information Systems |
| Depositing User: | AZAM GITA AMRULLAH |
| Date Deposited: | 20 Oct 2026 03:37 |
| Last Modified: | 20 Oct 2026 03:37 |
| URI: | http://eprints.perbanas.ac.id/id/eprint/14426 |
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