Tourism's trend Ranking on Social Media Data Using Fuzzy-AHP vs. AHP

TL;DR

This paper compares Fuzzy-AHP and AHP methods for ranking tourism attractions based on social media data, aiming to identify current trends and development priorities efficiently.

Contribution

It introduces a fuzzy-AHP approach for tourism trend ranking and compares its effectiveness with traditional AHP using social media data.

Findings

Fuzzy-AHP provides more accurate ranking with lower MSE.

Parks/Picnic Spots identified as top priority for development.

Fuzzy-AHP outperforms AHP in handling uncertain social media data.

Abstract

Tourism is an exciting thing to be visited by people in the world. Search for attractive and popular places can be done through social media. Data from social media or websites can be used as a reference to find current travel trends and get information about reviews, stories, likes, forums, blogs, and feedback from a place. However, if the search is done manually one by one, it takes a long time, and it becomes interesting to do research. So, searching based on current trends will be easier and faster. For this reason, this study uses a computer base to search by ranking tourist facilities from social media data or websites using the multi-criteria decision-making (MCDM) method. The implementation of the method used in finding the trend is the Fuzzy-AHP method in comparison with the AHP. The data used is data reviews, stories, likes, forums, blogs, and feedback from the web or social media. Because with these components, tourism can be developed according to visitors\'' wishes. The research aims to rank facilities\'' tourism attractions (trends) and development priorities. The priority and ranking used the fuzzy-AHP and AHP method to determine weight criteria and the ranking process. The highest ranking is on the Parks/Picnic Spots attraction, and make it a priority to develop. The methods have an average value MSE of all data is \approx 0.0002, which can be used for this ranking.