Analisis Minat Konsumen Terhadap Produk Makanan Pada Mie Gacoan Menggunakan Algoritma Decision Tree (Studi Kasus Mie Gacoan Rantau Prapat)

Abstract

This study was conducted to analyze consumer interest in Mie Gacoan Rantau Prapat using a Decision Tree-based classification method. This analysis aims to determine the most influential factors in determining consumer interest in the food product. The theoretical basis used is the concept of data mining with classification techniques, where Decision Tree was chosen because of its ability to produce easy-to-understand models. In addition, theories regarding model evaluation such as accuracy, precision, and recall are also used to measure the performance of the built classification. This research methodology includes collecting data from 100 consumer entries which are then divided using the Split Data feature in RapidMiner with a ratio of 60:40, resulting in 40 training data and 60 testing data. The classification process is carried out using the Decision Tree algorithm, while evaluation is carried out with the performance operator to assess the model results. The classification results show that cleanliness is a major factor in determining consumer interest, where the number of consumers in the Interest category is more dominant than the No Interest category. The model evaluation yielded an accuracy of 73.33% with a precision of 73.47% in the Interested class and 72.73% in the Not Interested class, as well as a recall of 92.31% in the Interested class and 38.10% in the Not Interested class. In conclusion, the classification model developed is able to provide a picture of consumer interest patterns with a fairly good level of accuracy. These results can be a strategic reference for Mie Gacoan to improve service quality and cleanliness as the main factors determining consumer interest.