ANALISIS DATA PENJUALAN HIJAB PREMIUM BERBASIS WEB MENGGUNAKAN ALGORITMA APRIORI UNTUK OPTIMASI STRATEGI PEMASARAN
Abstract
The rapid development of digital technology has driven an increase in online shopping transactions, including in the premium hijab label industry. Premium Hijab Label faces challenges in stock management, service delays, and difficulties in identifying consumer purchasing patterns. Therefore, this study aims to build a web-based sales analysis system by applying the Apriori algorithm as a data mining method to discover association patterns between products. The system development method used was prototyping, with stages including needs analysis, design, implementation using PHP with the CodeIgniter and MySQL frameworks, and testing using Black Box Testing. The analyzed data were Premium Hijab Label sales transactions from 2023–2024. The results show that the system can display frequent itemsets and generate association rules with certain support and confidence values. Some rules have confidence levels above 60%, which can be used as the basis for product recommendations and promotional strategies. The conclusion of this study is that the Apriori algorithm-based system can assist MSMEs in analyzing consumer shopping patterns, supporting strategic decision-making, and improving the efficiency of stock management and marketing.
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