Fuzzy Clustering and Association Rule for Improvement of Visitor Spots in the Lanna

• Main Authors: Jirawat Teyakome, Narissara Eiamkanitchat, Korawan Sangkakorn, Phichit Napook
• Format: Conference Proceeding
• Published: 2018
• Subjects: Computer Science; Decision Sciences; Engineering
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018297209&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/57095
• Institution: Chiang Mai University

© 2016 IEEE. This paper proposes the tool for the improvement of visitor spots of the Lanna civilization in the northern part of Thailand. Numbers of traveler are visited surrounding tourist spots in this area because of the identity of the culture, however large portions of the tourist attractions here still need to enhance to support the tourist. The propose tool expect to prescribe the subject to enhance for each individual tourist place. The fuzzy framework is used for clustering the features, and create the new values for each feature. The Apriori algorithm is applied and create the association rules. The outcomes demonstrate the connection of the criteria for the evaluated class of the visitor spots. All considered visitor spots in the Lanna civilization in the experiment are prior assessed by the specialists in the tourist study. Related person can use the experimental results as a guideline to improve their tourist attraction and able to estimate the class of their place as well.