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All Journal Majalah Geografi Indonesia Forum Geografi Journal of Applied Geospatial Information MAJALAH ILMIAH GLOBE Jurnal Geografi SmartComp The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Totok Wahyu Wibowo
Fakultas Geografi, Universitas Gadjah Mada
Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Physics Social Sciences Other

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Journal : Forum Geografi

 1 
Tourist Attraction Popularity Mapping based on Geotagged Tweets Wibowo, Totok Wahyu; Bustomi, Ahmad Faizan; Sukamdi, Anggito Venuary
Forum Geografi Vol 33, No 1 (2019): July 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i1.8021

Abstract

The development of tourist attractions is now highly influenced by social media. The speed at which information can be disseminated via the Internet has become an essential factor in enabling distinct tourist attractions to potentially gain high popularity in a relatively short time. This condition was not as prevalent several years ago when tourism promotion remained limited to a certain kind of media. As a consequence, rapid change in the relative popularity of tourist attractions is inevitable. Against this, knowledge of tourist attraction hotspots is essential in tourism management. This means there is a need to study how to both quickly determine the popularity level of tourist attractions and encompass a relatively large area. This article utilised tweet data from microblogging website Twitter as the basis from which to determine the popularity level of a tourist attraction. Data mining was conducted using Python and the Tweepy module. The tweet data were collected at the end of April and early May 2017, at times when there are several long holiday weekends. A Tweet Proximity Index (TPI) was used to calculate both the density and frequency of tweets based on a defined search radius. A Density Index (DI) was also used as a technique for determining the popularity. The results from both approaches were then compared to a random survey about people?s perceptions of tourist attractions in the study area. The result shows that geotagged tweet data can be used to determine the popularity of a tourist attraction, although it still only achieved a medium level of accuracy. The TPI approach used in this study produced an accuracy of 76.47%, while the DI achieved only 58.82%. This medium accuracy does indicate that the two approaches are not yet strong enough to be used for decision-making but should be more than adequate as an initial description. Further, it is necessary to improve the method of indexing and the exploration of other aspects of Twitter data.
Evidence Based Landslide Hazard Mapping in Purworejo using Information Value Model Approach Sudaryatno, Sudaryatno; Widayani, Prima; Wibowo, Totok Wahyu; Wiratmoko, Bagus; Nurbandi, Wahyu
Forum Geografi Vol 33, No 1 (2019): July 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i1.7592

Abstract

Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.
Tourist Attraction Popularity Mapping based on Geotagged Tweets Totok Wahyu Wibowo; Ahmad Faizan Bustomi; Anggito Venuary Sukamdi
Forum Geografi Vol 33, No 1 (2019): July 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i1.8021

Abstract

The development of tourist attractions is now highly influenced by social media. The speed at which information can be disseminated via the Internet has become an essential factor in enabling distinct tourist attractions to potentially gain high popularity in a relatively short time. This condition was not as prevalent several years ago when tourism promotion remained limited to a certain kind of media. As a consequence, rapid change in the relative popularity of tourist attractions is inevitable. Against this, knowledge of tourist attraction hotspots is essential in tourism management. This means there is a need to study how to both quickly determine the popularity level of tourist attractions and encompass a relatively large area. This article utilised tweet data from microblogging website Twitter as the basis from which to determine the popularity level of a tourist attraction. Data mining was conducted using Python and the Tweepy module. The tweet data were collected at the end of April and early May 2017, at times when there are several long holiday weekends. A Tweet Proximity Index (TPI) was used to calculate both the density and frequency of tweets based on a defined search radius. A Density Index (DI) was also used as a technique for determining the popularity. The results from both approaches were then compared to a random survey about people’s perceptions of tourist attractions in the study area. The result shows that geotagged tweet data can be used to determine the popularity of a tourist attraction, although it still only achieved a medium level of accuracy. The TPI approach used in this study produced an accuracy of 76.47%, while the DI achieved only 58.82%. This medium accuracy does indicate that the two approaches are not yet strong enough to be used for decision-making but should be more than adequate as an initial description. Further, it is necessary to improve the method of indexing and the exploration of other aspects of Twitter data.
Evidence Based Landslide Hazard Mapping in Purworejo using Information Value Model Approach Sudaryatno Sudaryatno; Prima Widayani; Totok Wahyu Wibowo; Bagus Wiratmoko; Wahyu Nurbandi
Forum Geografi Vol 33, No 1 (2019): July 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i1.7592

Abstract

Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.
Co-Authors Ahmad Faizan Bustomi Ambhika, Nafian Amelia Rizki Gita Paramanandi Anggito Venuary Sukamdi Arinalhaq Arinalhaq Bagus Wiratmoko Bernadeta Aurora Edwina Kumala Jati Bustomi, Ahmad Faizan Djati Mardiatno Dwiana Putri Setyaningsih Ernani Uswatun Khasanah Hubertus Ery Cantas Pratama Sutiono Muhammad Falakh Al Akbar Nurbandi, Wahyu Pratama, Abimanyu Putra Prima Widayani Sudaryatno Sudaryatno Sukamdi, Anggito Venuary Sunarto Sunarto Tri Wahyuni Wahyu Nurbandi Wirastuti Widyatmanti Wiratmoko, Bagus