MARKET BASKET ANALYSIS MENGGUNAKAN ALGORITMA APRIORI UNTUK STRATEGI PENJUALAN PRODUK BAHAN BANGUNAN DI CV ALBA

Husein Zidan; Ionia  Veritawati

Husein Zidan Universitas Pancasila
Ionia Veritawati Universitas Pancasila

Keywords: Market Basket Analysis, Quantitative Association Rules, Apriori Algorithm, Business Strategy, Product Bundling.

Abstract

This research is motivated by the decline in sales of HMD brand Concrete Roof tiles and the lack of
digitalization systems at CV ALBA during the period of 2024–2025. The decrease in sales indicates a
reduction in consumer purchasing interest toward HMD concrete roof tile products. Based on the results of
observations, the researcher applies Market Basket Analysis to address the purchasing decline in building
material products, and incorporates the concept of Quantitative Association Rules, as the dataset consists not
only of per-item product transactions but also includes purchase quantities integrated into the model. The
application of Market Basket Analysis is expected to provide solutions to the identified problem. The data
analyzed in this study comprises 1.000 transactions along with their purchase quantities, collected from
January 2024 to June 2025. The Apriori algorithm was applied using minimum support of 3%, minimum
confidence of 30%, and lift ratio > 1, resulting in 6.421 generated rules. From all the rules formed, the
researcher selected the top 3 best rules from 2-itemset to 7-itemset as key insights for product bundling sales
recommendations.