ANALISIS POLA PEMBELIAN DAN REKOMENDASI PRODUK  MENGGUNAKAN ALGORITMA APRIORI PADA SISTEM POINT OF SALE BERBASIS WEB

Wenti Ayu Wahyuni; Belsana Butar Butar; Muh. Nasirudin Karim

doi:10.51876/simtek.v11i2.1867

Authors

Wenti Ayu Wahyuni Program Studi Teknik Informatika, Fakultas Ilmu Komputer dan Kecerdasan Artifisial, Universitas Teknologi Mataram, Mataram, Indonesia
Belsana Butar Butar Program Studi Sistem Informasi, Universitas Bina Sarana Informatika, Jakarta, Indonesia
Muh. Nasirudin Karim Program Studi Rekayasa Sistem Komputer, Universitas Teknologi Mataram, Mataram, Indonesia

DOI:

https://doi.org/10.51876/simtek.v11i2.1867

Keywords:

Apriori Algorithm, Purchase Pattern Analysis, Association Rules, Point of Sale

Abstract

Retail businesses require an integrated transaction recording system supported by data analysis so that sales information can be effectively utilized in decision-making processes. This study aims to develop ApriPOS, a web-based point of sale system that implements the Apriori algorithm to identify purchasing patterns and generate product recommendations. The system was developed through several stages, including requirements analysis, data flow design, implementation of transaction, product, history, user, and dashboard modules, as well as the integration of association rule analysis. At the time of documentation, the database contained 55 transactions. Testing using a minimum support threshold of 7% and a minimum confidence threshold of 6% generated 44 association rules. The rule from 1 kg granulated sugar to 1 kg wheat flour achieved a support value of 33.96%, a confidence value of 100%, and a lift value of 2.944, while the rule from fried noodles to 1 L cooking oil achieved a support value of 66.04%, a confidence value of 100%, and a lift value of 1.514. ApriPOS integrates operational transaction processing with association information to support product bundling promotions, product placement strategies, and inventory planning.