ANALISIS DATA PENJUALAN HIJAB PREMIUM BERBASIS WEB MENGGUNAKAN ALGORITMA APRIORI UNTUK OPTIMASI STRATEGI PEMASARAN
Dublin Core
Title
ANALISIS DATA PENJUALAN HIJAB PREMIUM BERBASIS WEB MENGGUNAKAN ALGORITMA APRIORI UNTUK OPTIMASI STRATEGI PEMASARAN
Subject
Apriori Algorithm, Data Mining, Sales Analysis, Premium Hijab Label, E-commerce
Description
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
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
Creator
Taufik Hidayat, Yuni Handayani, Salma Thahira Adelia Heppy
Source
https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3358
Publisher
Institut Teknologi dan Bisnis Ahmad Dahlan
Date
2025-12-23
Contributor
Sri Wahyuni
Rights
E-ISSN : 2797-8516
Format
PDF
Language
Indonesian
Type
Text
Files
Collection
Citation
Taufik Hidayat, Yuni Handayani, Salma Thahira Adelia Heppy, “ANALISIS DATA PENJUALAN HIJAB PREMIUM BERBASIS WEB MENGGUNAKAN ALGORITMA APRIORI UNTUK OPTIMASI STRATEGI PEMASARAN,” Repository Horizon University Indonesia, accessed January 11, 2026, https://repository.horizon.ac.id/items/show/10251.