Paper Title
Revenue Optimization Using Booking Class Management Based On Traveler Behavior Analysis In Indonesian Airline

Abstract
To optimize revenue, airlines have to offer the right product, in the right time, for the right price. In order to do that, airlines have to understand their customer behavior. Traditional approach of one-type-fits-all product doesn’t suit anymore due to more complex and heterogeneous choices made by customers. Customer segmentation proposed to accommodate the problem in analyzing customer behavior. Customer segmentation results connected directly to the airline’s fare level that symbolized by the booking classes. This research will try to optimize revenue by using customer behavior segmentation and apply the segmentation result to the booking classes management. Segmentation will be done using K-Means clustering algorithm based on features defined. Data will be collected form airline's PNR database. The results show promising revenue increase. Keywords - Airlines, Customer Behavior, Customer Segmentation, K-Means Clustering, Revenue Management.