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All Journal G-Tech : Jurnal Teknologi Terapan
Ega Silfa Yuliana
Universitas Multimedia Nusantara, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Enhancing Marketing Strategies for Office Stationery Stores Using Equivalence Class Transformation Algorithms Ega Silfa Yuliana; Raymond Oetama
G-Tech: Jurnal Teknologi Terapan Vol 8 No 1 (2024): G-Tech, Vol. 8 No. 1 Januari 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i1.3441

Abstract

Office stationery stores facilitate operations for offices, schools, and businesses. However, the store owner must overcome the challenge of selecting the right products for promotion. This research aims to tackle this issue by comparing the performance of the Equivalence Class Transformation algorithms in discovering association rules using Support, confidence, and lift ratios. The findings reveal that the algorithm generates association rules based on Support, confidence, and lift values. Ten critical rules are identified, shedding light on algorithm effectiveness. Ultimately, this study underscores the significance of refining marketing approaches for brick-and-mortar stationery businesses and the value of data-driven methods in aiding decision-making. In the early promotion catalog phase, priority is assigned to rules with solid agreement by the Shop Owner, guiding the selection of featured items based on robust product associations.
Co-Authors Raymond Oetama