Data Analytics on Price Prediction of Travelling Package using Regression Models

Travel agencies set new prices on travel packages based on their experiences by analyzing the trend on holiday and festive season. However, they find it hard to set and predict exact travel packages with minimum prices to be offered for the upcoming years. Prices keep changing due to other reasons rather than the holiday and festive season. This research paper applied data analytics which is divided into two parts, 1) descriptive analytics to facilitate the agencies to have better insights of the data and 2) predictive analytics for price forecasting. Visualization is a part of descriptive analytics where dispersion and correlation of data are produced to gain insight of data. Meanwhile, in the predictive analytics part, Linear Regression and Multiple Linear Regression models are applied to predict the price of travel packages. Different parameter settings are applied to optimize the score of R-square. Hence, the final result of 0.9346 R-square is achieved by applying Multiple Linear Regression with all variables are taken into consideration.