The Development of a Recommender System for Online Travel Insurance by using Intuitionistic Fuzzy Sets based on Gray Relational Analysis

Abstract

The travel insurance is one of the main incomes of online insurance brokers. The online travel insurance recommendation system is a tool that helps the companies create competitive advantage in business by providing customers with recommendations to buying a suitable travel insurance plan for their needs and reduces the hassle of decision-making to buy travel insurance as a result of diverse coverage. At present, there is still no development of recommender system for purchasing online travel insurance. Thus, the objective of the research aimed to design and develop the recommender system for consumers to buy travel insurance by using Intuitionistic Fuzzy Sets base on Gray Relational Analysis. Intuitionistic Fuzzy Sets are applied to determine weight of each criterion which indicates the important level of coverage and the weights are taking into account for Multiple Criteria Decision-Making by using Gray Relationship Analysis Method. The experimental results showed that the sample of 40 people who employed the mentioned recommender system satisfied all aspects in a high level. Furthermore, at least 70% of recommendations retrieved by the recommender system match to the travel insurance plan chosen by the sample.