Data Classification Algorithm Based on Association Rules from the Perspective of Data Mining

Liu, Hongxing; Shu, Qijiang; Xiong, Hongyan; Yang, Yuzhu

doi:10.1109/ickecs56523.2022.10060274

Cited by 1 publication

(1 citation statement)

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“…Rule dengan nilai kepercayaan tinggi tetapi support rendah mungkin tidak signifikan secara keseluruhan. Oleh karena itu, kedua metrik ini seringkali dipertimbangkan dalam analisis asosiasi untuk menemukan rule yang paling relevan dan dapat diterapkan dalam konteks bisnis atau penelitian (Liu et al, 2022).…”

Section: Association Ruleunclassified

Penerapan Association Rule-Market Basket Analysis (AR-MBA) Dalam Menentukan Strategi Product Bundling: Studi Kasus Pada Minimarket AKPRIND MART

Mustofa,

Wibowo,

Sekarjati

et al. 2024

JUTIN

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Data has become the most valuable component to be processed in order to provide usable information in the modern world of rapidly developing technology. When it comes to more in-depth or clear data analysis, technology is quite useful. Real governmental, social, and commercial operations use this technology; in the case of business, this is demonstrated by the quantity of minimarkets operating throughout Indonesia. As a result, it greatly increases commercial competition. Consequently, in order to compete, a study using the available data must be conducted. The Association Rule-Market Basket Analysis method was employed in this study to ascertain the shopping interests of the participants. According to the study's findings, two rules 60% (washing equipment and foodstuffs) and 62% (medicine and bottled drinks) showed the greatest confidence values. Based on these findings, the minimarket can decide what has to be done in terms of Product Bundling, setting up the layout and other tasks

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Section: Association Ruleunclassified