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All Journal Jurnal Dedikasi DINAMIKA DOTCOM TEKNOLOGI INFORMASI Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA Jurnal Ilmiah KOMPUTASI J I M P - Jurnal Informatika Merdeka Pasuruan JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) PEDULI: Jurnal Imiah Pengabdian Pada Masyarakat Jurnal Ekonomi Pembangunan JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) G-Tech : Jurnal Teknologi Terapan Jurnal Ekonomi Pembangunan JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Sujito Sujito
STMIK PPKIA Pradnya Paramita
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences

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Analysis of Milkshake Beverage Sales using Apriori Algorithm Sujito, Sujito; Idris, Muhammad; Kadir, Shaifany Fatriana; Nurdiyansyah, Firman
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 2 (2025): June
Publisher : Lumina Infinity Academy Foundation

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Abstract

This research discusses the application of Data Mining with the Apriori algorithm on milkshake drink sales to support Business Intelligence. The research process includes collecting sales transaction data, forming frequent itemsets, and analyzing association rules using metrics such as support and confidence. The results show that product combinations, such as Chocolate and Strawberry, have high purchase rates with support reaching 75% and confidence up to 75%. These findings provide important insights for business owners in designing more effective marketing strategies, including promotions and stock management optimization. By utilizing the Apriori algorithm, this research successfully identified significant purchase patterns that can drive growth and improve customer satisfaction in the food and beverage industry.
Application of Apriori Algorithm to Find Flower Purchase Patterns Tusianto, Daffa Yauzan; Fairuzabadi, Ahmad; Sujito, Sujito
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 3 (2025): October
Publisher : Lumina Infinity Academy Foundation

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Abstract

This research aims to apply the Apriori algorithm in analyzing flower purchase patterns at a flower shop. Apriori algorithm is used to identify product combinations that are often purchased together, in the hope of finding purchasing patterns that can be utilized to improve marketing strategies and store operational efficiency. Transaction data from the shop is processed to extract frequent itemsets and generate association rules by setting the right threshold of support and confidence values. The results of this study show that flower combinations such as Tulip and Bougenville frequently co-occur in purchases, with significant support-confidence products. These findings provide insights into consumer purchasing behavior that can be used to recommend product bundling or product rearrangement in stores. This research contributes to the application of data mining in the retail sector, particularly in increasing sales and customer satisfaction in flower shops.
Co-Authors Abd. Rasyid Syamsuri Ahmad Fairuzabadi Balandra, Daniel Dwi Eka Yuniar Eni Farida Fatriana Kadir, Shaifany Firman Nurdiyansyah, Firman Galih Mahendra Heri Apriyanto Ida Ayu Putu Sri Widnyani Indah Dwi Mumpuni Istikhomah Istikhomah, Istikhomah Khoerul Anwar Lesa Ahsanti Ruma Liduina Asih Primandari, Liduina Asih Mahmud Yunus Mahmud Yunus Mohamad As'ad Mohamad As’ad Muhammad Idris Mukhamad Fatkhur Roji Nensy Enlanda Putri Pratama Nirwan Moka Prapcoyo, Hari Rahayu Widayanti Retno Sundari Sigit Setyowibowo Sigit Setyowibowo Sri Esti Trisno Sami Teguh Purnomo, Teguh Tusianto, Daffa Yauzan