Implementation of Data Mining of Organic Vegetable Sales With Apriori Algorithm
Abstract
In the modern organic vegetable sector, the author observes that there is very tight business competition. Therefore, an effective approach is essential to attract buyers, although restricted sources of new information are one of the hurdles in establishing this business.Association rules are expressed with numerous features that are commonly referred to as (affinity analysis) or (market basket analysis. It was discovered that if consumers buy curly red chilies, they are also inclined to buy cayenne pepper with a 100% confidence level. Likewise, if people buy kale and red curly chiles, they are more likely to buy cayenne pepper with a 100% confidence level. This also applies if consumers buy tomatoes and curly red chilies with a 100% confidence level. In addition, other associations were also observed, such as if consumers buy curly red chilies, they prefer to buy tomatoes with a confidence level of 86%, or if they buy tomatoes and bird's eye chilies, they tend to buy curly red chiles with an 86% confidence level.Likewise, if people buy both cayenne pepper and red curly chili, they are more likely to buy tomatoes with an 86% confidence level. Finally, if customers buy kale and cayenne pepper, they are also likely to buy red curly chilies at an 83% confidence level. Based on the data acquired from this study, it is intended to obtain information about combinations of organic veggies that consumers typically buy together in each transaction, with the intention of improving organic vegetable yields and devising appropriate sales tactics.
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