Coffee Quality Classification Based on Customer Reviews Using C4.5 Algorithm - Siahaan, Ricardo Fransdoli; Muliono, Rizki (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING, 2025)
Coffee is a very popular commodity throughout the world, and its quality is oken evaluated through customer reviews. This research aims to classify coffee quality based on reviews given by consumers using the C4.5 algorithm. C4.5 is a machine learning algorithm used to generate decision trees, which allows decision making based on relevant attributes. In this research, the data used consists of customer reviews taken from e-commerce plaVorms and coffee discussion forums. The data is then processed with natural language processing (NLP) techniques to extract important features such as sentiment, keywords and term frequency. These features are used as input for the C4.5 algorithm, which builds a classification model based on patterns contained in the data. The results of the research show that the C4.5 model is able to classify coffee quality with high accuracy, reaching up to 85%. The factors that most influence quality classification include taste, aroma, and packaging, which are frequently mentioned in reviews. In addition, the analysis also shows significant differences in the quality of coffee produced from different coffee producing regions, which can provide insight for producers to improve their products.