The aviation industry is growing very significantly due to increased mobility, economic expansion and current technological advances. However, as mobility increases and the number of airline passengers increases, airlines experience problems in overcoming flight schedule delays or in other words delays. Data analysis plays an important role in processing large amounts of data to find hidden insights in data. The aim of writing this service journal is to identify days with the highest average minutes of delay, months that experience the highest average delays, and at what times flight delays often occur. . This service object uses secondary data obtained from the Kaggle site. It is hoped that this journal can be used as material for consideration in decision making and improving the operational performance of each airline involved.