2018International Journal of Engineering & TechnologyOpen access

Implementation of Apriori Algorithm for Determining Purchase Patterns in One Transaction

Murnawan Murnawan, Ardiles Sinaga, Ucu Nughraha

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Abstract

The organization data owned is one of the assets of the organization. With the daily operational activities, the longer the data will increase. By using techniques that can do data processing, these data can be obtained important information that can be used for future developments. Association rules are one of these techniques which aims to find patterns in the form of products that are often purchased together or tend to appear together in a transaction from transaction data which is generally very large by using the concept association rules themselves derived from Market Basket Analysis terminology, namely search for relationships from several products in a purchase transaction. In designing this application will build applications that classify the data items based on the tendency to appear together in a transaction using the Apriori Algorithm. The Apriori algorithm is the first algorithm and is often used to find association rules in data mining applications with association rule techniques.

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What this paper is about

The organization data owned is one of the assets of the organization. With the daily operational activities, the longer the data will increase. By using techniques that can do data processing, these data can be obtained important information that can be used for future developments. Association rules are one of these techniques which aims to find patterns in the form of products that are often purchased together or tend to appear together in a transaction from transaction data which is generally very large by using the concept association rules themselves derived from Market Basket Analysis terminology, namely search for relationships from several products in a purchase transaction. In designing this application will build applications that classify the data items based on the tendency to appear together in a transaction using the Apriori Algorithm. The Apriori algorithm is the first algorithm and is often used to find association rules in data mining applications with association rule techniques.

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Available abstract

The organization data owned is one of the assets of the organization. With the daily operational activities, the longer the data will increase. By using techniques that can do data processing, these data can be obtained important information that can be used for future developments. Association rules are one of these techniques which aims to find patterns in the form of products that are often purchased together or tend to appear together in a transaction from transaction data which is generally very large by using the concept association rules themselves derived from Market Basket Analysis terminology, namely search for relationships from several products in a purchase transaction. In designing this application will build applications that classify the data items based on the tendency to appear together in a transaction using the Apriori Algorithm. The Apriori algorithm is the first algorithm and is often used to find association rules in data mining applications with association rule techniques.

Key concepts: Apriori algorithm, Association rule learning, Database transaction, Transaction data, Computer science, Terminology, Data mining, Affinity analysis

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