Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4960459 | Procedia Computer Science | 2017 | 8 Pages |
Abstract
Tourism has been an irreplaceable part of economy growth of every country. By that factor, the authors were encouraged to build an application to serve detail information of tour destinations to provide easy preparation for travelling. The application, TripBuddy, was developed to learn user's behavior based on empiric data, which used to offer relevant destinations to certain user by using K-Means Clustering. TripBuddy is a web-based application which suggests optimal route with detail information of destinations, schedule, cost and duration to ease user's travel plan and it also gives recommendation based on user's browsing behavior
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Merlinda Sumardi, Jufery Jufery, Frenky Frenky, Rini Wongso, Ferdinand Ariandy Luwinda,