MODEL KLASIFIKASI KEPUASAN KONSUMEN MASKAPAI PENERBANGAN XYZ MENGGUNAKAN ALGORITMA DECISION TREE - Gabriel Britania (2021)
The great interest of airline consumers in this era is caused by the very rapid development of air transportation. This is due to technological developments in the field of aviation and the world economy. The impact of this development has made airlines more aggressive in providing air transportation services. Research on the prediction of customer satisfaction requires high accuracy in estimating satisfied or dissatisfied consumers with an airline. Therefore this research focuses on these problems by using the Machine Learning model with the Decision Tree Algorithm. In the data classification process, cleaning is required through the preprocessing process. After that, the data is extracted and the attributes are selected so that the data is ready to be used to train machine learning. Confusion Matrix evaluation results with 70% training data and 30% test data produce 94% accuracy and 93% Recall. From the research results, consumer satisfaction factors are strongly influenced by Inflight Entertainment, Seat Comfort, Easy of Online Booking, Customer Type_Disloyal Customer. This is obtained by finding the highest gain value for each attribute. The highest gain is used as the Root Node of the decision tree.