Aji, Galih Wasito (2022) Data Mining Implementation For Product Transaction Patterns Using Apriori Method. SinkrOn (Jurnal & Penelitian Teknik Informatika), 8 (1). pp. 421-432. ISSN 2541-2019
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Abstract
In the era of information technology, entrepreneurs must have a good marketing strategy so that profits do not decrease. The decline in profits is happening at fast food restaurants for example fast food restaurants in Gresik city. This is due to the incompatibility of products sold with customers in Gresik city. Many promos given by marketing didn’t go well, resulting in sales targets not being achieved. To overcome this, good sales data analysis is needed to get products that match with type of customer. Using data mining with the Apriori algorithm is very appropriate for looking customer purchasing patterns. Association rules that are formed with support and confidence as benchmarks provide, a good reference regarding customer purchasing patterns. Research at fast food restaurant in Gresik was conducted by taking transaction data from September 2021 - September 2022 totaling 48,750 transactions with 134 transactions/day. The results of the research are customer buying patterns that are formed in 10 rules with highest percentage. The best rules that can be the best promos is: if customers buy Rice then buy Drinks with 11,19% support and 68,1% confidence. From the results of research that has been done, customer purchasing patterns have been obtained and can be used as a reference by marketing.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Apriori Algorithm, Association Rules, Data Mining, Marketing strategy, Purchasing Pattern |
| Subjects: | Engineering > Informatics Engineering Engineering |
| Divisions: | Faculty of Engineering > Informatics Engineering Study Program |
| Depositing User: | Galih Wasito Aji |
| Date Deposited: | 09 Mar 2023 03:04 |
| Last Modified: | 09 Mar 2023 03:04 |
| URI: | http://eprints.umg.ac.id/id/eprint/7084 |
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