Sales Pattern Identification for Marketing Strategies Using Data Mining

Mawadati, Argaditia and Emaputra, Andrean and Sekarjati, Kartinasari Ayuhikmatin (2021) Sales Pattern Identification for Marketing Strategies Using Data Mining. The 2nd International Conference on Engineering Science and Technology (ICEST) 2021.

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The development of the culinary business, such as food stalls, is increasing rapidly. This causes the competition to become even tighter. Food stalls must have targeted and precise strategies to survive and compete. Identifying the customer’s preference is one of the strategies that can increase sales and retain customers. The customer’s preference can be observed through purchase transaction data. Observation of sales transaction data in a simple way does not always get effective results because of the large volume of data processed and the difficulty in finding the association between one menu sales and another. With data mining, this problem can be overcome. In this study, the data mining method used is the Apriori Algorithm. The application of the apriori algorithm helps in forming candidate item combinations that may occur. Thus, it can be seen the relationship between the combination of menus that are sold, whether including the most frequently sold or not. This information can be taken into consideration to determine the next marketing strategies

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Fakultas Teknologi Industri > Teknik Industri (S1)
Depositing User: Argaditia Mawadati
Date Deposited: 29 Jan 2022 17:17
Last Modified: 29 Jan 2022 17:17

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