IMPLEMENTASI ALGORITMA APRIORI PADA DATA MINING UNTUK MENENTUKAN STRATEGI PENJUALAN DENGAN MENGGUNAKAN DATA TRANSAKSI
Keywords:
Data Mining, Strategy, Promotion, Recommendation, Website, Apriori Algorithm, Association RuleAbstract
The development of the food and beverage culinary industry is growing rapidly. Make food and beverage business owners, especially restaurants. Having to make the right decisions to survive in the competition in the era of digital market development, restaurant owners must always be ready to innovate while still being able to meet consumer needs through products that can attract customers that can boost sales. Stored transaction data has information that can be extracted using data mining techniques, for example, by knowing the pattern of sales in purchases by consumers. Information about sales patterns can be used by Lampoh Coffee to create more potential promotional strategies to increase sales by referring to items (menus) that are often purchased together. The method used is the a priori algorithm method, which produces association rules in the form of patterns that occur in transaction data so that consumers can find out what items or products are purchased simultaneously by consumers. The purpose of this research is a website-based application to analyze the buying pattern (association rule) by consumers. Where the buying pattern can be used as a recommendation in determining the promotion development strategy.
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