Implementation Of Data Mining With C4.5 Algorithm For Determining The Home Industry Product Marketing Strategy

Teresia Herniamwati Zebua (STMIK Pelita Nusantara)
Fristi Riandari (STMIK Pelita Nusantara)

Journal of Intelligent Decision Support System (IDSS)
Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)

me Industry is one of the SMEs that produce home-made products, such as pastries. Not all of these products are sold by consumers. This study uses a web-based C4.5 algorithm to determine marketing strategies for Home Industry products that are not selling well by classifying the indicators that most influence consumers in buying Home Industry products so that they can provide information about marketing strategies that will be carried out. Based on the results of the study, the highest gain value was the packaging attribute with a value of 1.86, so that the packaging attribute was used as the root in the formation of a decision tree. Then the second highest gain is the price attribute with a value of 1.26, and the third highest gain is the taste attribute with a value of 1.03, then the fourth highest gain is the service attribute with a value of 0.89.