Tourism Trend Mapping Based on Social Media Using SAW Algorithm
Indonesia is a country that has a variety of places to hold holidays. Having a plan about the most popular tourist attractions is the key for everyone who wants to travel to an area. But data on tourist spots that are currently in trend are often not easily obtained. Different from tour agents who a...
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| Published in | Journal of physics. Conference series Vol. 1140; no. 1; pp. 12041 - 12048 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Bristol
IOP Publishing
01.12.2018
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Indonesia is a country that has a variety of places to hold holidays. Having a plan about the most popular tourist attractions is the key for everyone who wants to travel to an area. But data on tourist spots that are currently in trend are often not easily obtained. Different from tour agents who already have a lot of experience and data without fear of missing information. therefore, presenting the tourism trends in a particular group is almost impossible to use data on the number of frequented places. This paper will discuss tourism trends that have appeal based on social media, with case studies on Twitter data with certain regional fields. Social media provides large raw data including travelers' choices when they visit the venue. however, the data obtained is not shaped in human language. These results will be processed first and will be arranged to determine the level of tourist destinations are often visited. The algorithm used to process using Simple Additive Weighting (SAW) is proposed to arrange food ranking. To measure accuracy, we compared our results with tourist sights in Yogyakarta. |
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| AbstractList | Indonesia is a country that has a variety of places to hold holidays. Having a plan about the most popular tourist attractions is the key for everyone who wants to travel to an area. But data on tourist spots that are currently in trend are often not easily obtained. Different from tour agents who already have a lot of experience and data without fear of missing information. therefore, presenting the tourism trends in a particular group is almost impossible to use data on the number of frequented places. This paper will discuss tourism trends that have appeal based on social media, with case studies on Twitter data with certain regional fields. Social media provides large raw data including travelers' choices when they visit the venue. however, the data obtained is not shaped in human language. These results will be processed first and will be arranged to determine the level of tourist destinations are often visited. The algorithm used to process using Simple Additive Weighting (SAW) is proposed to arrange food ranking. To measure accuracy, we compared our results with tourist sights in Yogyakarta. |
| Author | Setyanto, A Maulana, M A Oktavia Habib, M |
| Author_xml | – sequence: 1 givenname: M A surname: Maulana fullname: Maulana, M A email: muhammad.0874@students.amikom.ac.id organization: Magister of Information Engineering, University of Amikom Yogyakarta , Indonesia – sequence: 2 givenname: M surname: Habib fullname: Habib, M organization: Magister of Information Engineering, University of Amikom Yogyakarta , Indonesia – sequence: 3 givenname: A surname: Setyanto fullname: Setyanto, A organization: Magister of Information Engineering, University of Amikom Yogyakarta , Indonesia – sequence: 4 surname: Oktavia fullname: Oktavia organization: Bachelor of Information Engineering, University of Amikom Yogyakarta , Indonesia |
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| Cites_doi | 10.1109/SIET.2017.8304106 10.1016/j.eswa.2013.01.019 |
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| Title | Tourism Trend Mapping Based on Social Media Using SAW Algorithm |
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