http://www.iaeme.com/IJMET/index.asp 1448 editor@iaeme.com International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 13, December 2018, pp. 1448–1457, Article ID: IJMET_09_13_144 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=9&IType=13 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed WORTH EAT II: AN EXTENDED INTELLIGENT APPLICATION FOR FINDING RESTAURANT Ditdit Nugeraha Utama Computer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480 Titik Handayani, Dara Kumala Devi, Ellin Lasona Putri and Wahyu Ramadhan Information System, Universitas Mercu Buana, Jakarta, Indonesia, ABSTRACT Worth Eat II (WE2) is an extended version of Worth Eat application. It is and intelligent application for recommending the appropriate restaurant based on its customers’ characteristics. Three previous parameters (i.e. interest, location, and restaurant rating) were academically expanded via extending the parameter restaurant rating to become two derivative types of rating (i.e. taste and cleanliness rating) and adding other parameter food price. Fuzzy-Euclidean (fuzzy logic and Euclidean distance combination) is a main method operated in this study; where the distance calculation value benefitted to determine the fittest value. Then, hill-climbing optimization method was functioned to seek the decision suitable value. Finally, the intelligent model was technically constructed on Android environment which is able to be accessed by customers via their mobile-device. Keywords: Worth Eat application, parameter food price Cite this Article: Ditdit Nugeraha Utama, Handayani, Dara Kumala Devi, Ellin Lasona Putri and Wahyu Ramadhan, Worth Eat Ii: an Extended Intelligent Application for Finding Restaurant, Journal of Mechanical Engineering and Technology, 9(13), 2018, pp. 1448– 1457 http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=9&IType=13 1. INTRODUCTION Particularly in new area visited or in road-traffic congestion position, the recommendation of restaurant to visit is practically necessitated. Moreover, the food is an individual passion and has a specified customer [1]. Thus, the mobile recommender application to suggest the most suitable restaurant for the customers is rationally beneficial and valuable. Various researches in intelligent model/application domain which implemented in numerous business areas and cases were performed. Some of them are [2], [3], [4], and [5]. A technical environment for intelligent application in mobile device was proposed. The environment was constructed to answer two types of issue; memory and processing power, and diversity of mobile