Consumer Satisfaction Analysis at Inos Coffee & Kitchen Using the C4.5 Algorithm

Abstract

Consumer satisfaction is one of the important elements for the success of a business, especially in the culinary sector like Inos Coffee & Kitchen. This research is essential to explore the factors affecting consumer satisfaction, identify dominant factors such as service quality and comfort of the place, and generate decision rules that can assist management in formulating strategies to improve services and products. Several of these factors can be studied using the C4.5 algorithm, which is one of the decision tree methods in data mining. The data used in this study was obtained through a consumer satisfaction survey covering several variables, including food quality, service, price, atmosphere, and comfort of the place. The C4.5 algorithm is applied to build a model that can identify the most influential variables on consumer satisfaction. Furthermore, the results of this study support more accurate data-driven decision-making. The findings indicate that service quality and comfort of the place are dominant factors determining customer satisfaction at Inos Coffee & Kitchen. Additionally, the application of the C4.5 algorithm successfully generated rules that can serve as guidelines for management in making better decisions to enhance consumer satisfaction. This research is expected to assist Inos Coffee & Kitchen management in formulating more effective strategies to increase customer loyalty and contribute to the application of data mining technology in the culinary industry. This study expands the application of the C4.5 algorithm, which is typically used in data classification, into the context of the culinary industry to predict and understand factors influencing customer satisfaction. It adds relevant real case studies demonstrating how this algorithm can produce practical decision rules that are easy for businesses to implement.