“TripBuddy” Travel Planner with Recommendation based on User‘s Browsing Behaviour | Zendy

Merlinda Sumardi | Zendy; Jufery | Zendy; Frenky | Zendy; Rini Wongso | Zendy; Ferdinand Ariandy Luwinda | Zendy

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“TripBuddy” Travel Planner with Recommendation based on User‘s Browsing Behaviour

Author(s) -

Merlinda Sumardi,

Jufery,

Frenky,

Rini Wongso,

Ferdinand Ariandy Luwinda

Publication year - 2017

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2017.10.084

Subject(s) - computer science , planner , schedule , destinations , tourism , cluster analysis , recommender system , plan (archaeology) , duration (music) , world wide web , factor (programming language) , artificial intelligence , art , literature , archaeology , political science , law , history , programming language , operating system

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

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