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Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites

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@article{IJASEIT10686,
   author = {Dyah Lestari Widaningrum and Isti Surjandari and Dodi Sudiana},
   title = {Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {10},
   number = {6},
   year = {2020},
   pages = {2213--2221},
   keywords = {tourism; tourism support facilities; spatial analysis; co-location pattern mining; network graph.},
   abstract = {

Tourism is continuously developing as a new economic source in Indonesia. Tourism activities extend to the various services, products, and experiences provided in the tourism site’s surrounding area. Tourism development requires information on possible related activities with tourism. However, there was a lack of studies that examined the relationship between tourism sites and the simultaneous presence of multiple public facilities, which would reveal the value of proximity. This paper aims to investigate the proximity patterns of tourism sites and the support facilities, to develop a strategy for tourism sites. The average nearest-neighbor results verify that there are clustering tendencies for almost all datasets. The Kernel Density Estimation (KDE)-based raster’s were created to visualize the patterns of tourism sites and nearby public facilities, which located near three world cultural heritage sites in Indonesia. Co-location pattern mining was applied to examine the co-location behavior between tourism sites and tourism support facilities using the Participation Index (PI) as the measurement parameter. This study provides knowledge, specifically the existence of co-location rules between tourism sites and tourism support facilities, which consist of food services, accommodations, transportation, shopping, and other tourism support facilities. The network graph shows that the location of tourism support facilities can be affected by the types of tourism sites, providing practical implications for individuals, business owners, and policymakers. Government policies related to planning for tourism destination development that consider the characteristics of spatial interactions are expected to be able to support government targets for increasing lengths of stay and tourist expenditures.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10686},    doi = {10.18517/ijaseit.10.6.10686} }

EndNote

%A Widaningrum, Dyah Lestari
%A Surjandari, Isti
%A Sudiana, Dodi
%D 2020
%T Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites
%B 2020
%9 tourism; tourism support facilities; spatial analysis; co-location pattern mining; network graph.
%! Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites
%K tourism; tourism support facilities; spatial analysis; co-location pattern mining; network graph.
%X 

Tourism is continuously developing as a new economic source in Indonesia. Tourism activities extend to the various services, products, and experiences provided in the tourism site’s surrounding area. Tourism development requires information on possible related activities with tourism. However, there was a lack of studies that examined the relationship between tourism sites and the simultaneous presence of multiple public facilities, which would reveal the value of proximity. This paper aims to investigate the proximity patterns of tourism sites and the support facilities, to develop a strategy for tourism sites. The average nearest-neighbor results verify that there are clustering tendencies for almost all datasets. The Kernel Density Estimation (KDE)-based raster’s were created to visualize the patterns of tourism sites and nearby public facilities, which located near three world cultural heritage sites in Indonesia. Co-location pattern mining was applied to examine the co-location behavior between tourism sites and tourism support facilities using the Participation Index (PI) as the measurement parameter. This study provides knowledge, specifically the existence of co-location rules between tourism sites and tourism support facilities, which consist of food services, accommodations, transportation, shopping, and other tourism support facilities. The network graph shows that the location of tourism support facilities can be affected by the types of tourism sites, providing practical implications for individuals, business owners, and policymakers. Government policies related to planning for tourism destination development that consider the characteristics of spatial interactions are expected to be able to support government targets for increasing lengths of stay and tourist expenditures.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10686 %R doi:10.18517/ijaseit.10.6.10686 %J International Journal on Advanced Science, Engineering and Information Technology %V 10 %N 6 %@ 2088-5334

IEEE

Dyah Lestari Widaningrum,Isti Surjandari and Dodi Sudiana,"Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites," International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 6, pp. 2213-2221, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.6.10686.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Widaningrum, Dyah Lestari
AU  - Surjandari, Isti
AU  - Sudiana, Dodi
PY  - 2020
TI  - Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 6
Y2  - 2020
SP  - 2213
EP  - 2221
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - tourism; tourism support facilities; spatial analysis; co-location pattern mining; network graph.
N2  - 

Tourism is continuously developing as a new economic source in Indonesia. Tourism activities extend to the various services, products, and experiences provided in the tourism site’s surrounding area. Tourism development requires information on possible related activities with tourism. However, there was a lack of studies that examined the relationship between tourism sites and the simultaneous presence of multiple public facilities, which would reveal the value of proximity. This paper aims to investigate the proximity patterns of tourism sites and the support facilities, to develop a strategy for tourism sites. The average nearest-neighbor results verify that there are clustering tendencies for almost all datasets. The Kernel Density Estimation (KDE)-based raster’s were created to visualize the patterns of tourism sites and nearby public facilities, which located near three world cultural heritage sites in Indonesia. Co-location pattern mining was applied to examine the co-location behavior between tourism sites and tourism support facilities using the Participation Index (PI) as the measurement parameter. This study provides knowledge, specifically the existence of co-location rules between tourism sites and tourism support facilities, which consist of food services, accommodations, transportation, shopping, and other tourism support facilities. The network graph shows that the location of tourism support facilities can be affected by the types of tourism sites, providing practical implications for individuals, business owners, and policymakers. Government policies related to planning for tourism destination development that consider the characteristics of spatial interactions are expected to be able to support government targets for increasing lengths of stay and tourist expenditures.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10686 DO - 10.18517/ijaseit.10.6.10686

RefWorks

RT Journal Article
ID 10686
A1 Widaningrum, Dyah Lestari
A1 Surjandari, Isti
A1 Sudiana, Dodi
T1 Spatial Characteristic of Tourism Sites on Neighborhood Support Facilities and Proximities in Cultural World Heritage Sites
JF International Journal on Advanced Science, Engineering and Information Technology
VO 10
IS 6
YR 2020
SP 2213
OP 2221
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 tourism; tourism support facilities; spatial analysis; co-location pattern mining; network graph.
AB 

Tourism is continuously developing as a new economic source in Indonesia. Tourism activities extend to the various services, products, and experiences provided in the tourism site’s surrounding area. Tourism development requires information on possible related activities with tourism. However, there was a lack of studies that examined the relationship between tourism sites and the simultaneous presence of multiple public facilities, which would reveal the value of proximity. This paper aims to investigate the proximity patterns of tourism sites and the support facilities, to develop a strategy for tourism sites. The average nearest-neighbor results verify that there are clustering tendencies for almost all datasets. The Kernel Density Estimation (KDE)-based raster’s were created to visualize the patterns of tourism sites and nearby public facilities, which located near three world cultural heritage sites in Indonesia. Co-location pattern mining was applied to examine the co-location behavior between tourism sites and tourism support facilities using the Participation Index (PI) as the measurement parameter. This study provides knowledge, specifically the existence of co-location rules between tourism sites and tourism support facilities, which consist of food services, accommodations, transportation, shopping, and other tourism support facilities. The network graph shows that the location of tourism support facilities can be affected by the types of tourism sites, providing practical implications for individuals, business owners, and policymakers. Government policies related to planning for tourism destination development that consider the characteristics of spatial interactions are expected to be able to support government targets for increasing lengths of stay and tourist expenditures.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10686 DO - 10.18517/ijaseit.10.6.10686