Erlan Fauzi Reza, . (2025) SISTEM INFORMASI PENJUALAN MELALUI IDENTIFIKASI POLA PEMBELIAN KONSUMEN PADA DATA TRANSAKSI KAFE DENGAN ALGORITMA FP-GROWTH. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The rapid growth of technology has encouraged businesses to adopt digital innovations to improve efficiency and effectiveness, including in the food and beverage industry. Two Much Coffee & Roastery is a café that still operates in a semi-digital way, where transactions are recorded manually using Microsoft Excel. The cafe faces challenges in optimizing its sales strategy, especially in applying a cross selling strategy, because there is no system that can suggest products automatically. This study aims to use a data mining technique called association rules with the FP-Growth algorithm to find patterns in customer purchases based on past transaction data. The algorithm was applied with a minimum support value of 0.01 and a minimum lift value of 1.0, resulting in 30 association rules. These rules were then implemented into a web-based information system designed for cashier use to support the cross selling strategy. This system not only records transactions but also provides product recommendations based on previous purchasing patterns, which is expected to help the café increase sales more effectively and efficiently.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2110512109] [Pembimbing 1: Iin Ernawati] [Pembimbing 2: Nindy Irzavika] [Penguji 1: Catur Nugrahaeni Puspita Dewi] [Penguji 2: Bambang Tri Wahyono] |
| Uncontrolled Keywords: | FP-Growth, Data Mining, Cross Selling, Association Rules, Information System |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | ERLAN FAUZI REZA |
| Date Deposited: | 06 Aug 2025 07:49 |
| Last Modified: | 06 Aug 2025 07:49 |
| URI: | http://repository.upnvj.ac.id/id/eprint/37414 |
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