Pub Date : 2021-11-01DOI: 10.23917/forgeo.v35i2.14003
R. M. Nisaa', J. Sartohadi, D. Mardiatno
Some cities in Indonesia which are located on Southern Java Island are susceptible to tsunamis. However, the application of participatory GIS for the assessment of building vulnerability to tsunamis remains rarely evaluated. The aims of this research are 1) to obtain the parameters of building vulnerability to tsunamis using the participatory approach, and 2) to evaluate the results of building vulnerability assessment using participatory GIS. A tsunami inundation map was constructed based on numerical modelling using the Hawke's Bay equation. Participatory approaches were taken to establish the parameters that affect the vulnerability of buildings to tsunamis using in-depth interviews. Respondents were selected using the purposive sampling technique. A geographic information system (GIS) was then applied to build a geodatabase and to perform analysis. The results show that six parameters were obtained from local people’s participation, namely building materials, the number of stories of the buildings , orientation, preservation condition, building row, and natural barriers. All the parameters were identified and interpreted using aerial photos. A field survey was conducted to complete the information on building characteristics. Many buildings near the beach were classified as having high and moderate vulnerability. The main benefit of participatory GIS is that the role of the community makes a significant contribution to providing vulnerability information. It also raises public awareness and improves preparedness for disaster risk management. The drawback is that parameters based on participatory approaches are dynamic and may be different in other areas.
{"title":"Participatory GIS Approach to Assessing Building Vulnerability to Tsunamis in Pangandaran Regency","authors":"R. M. Nisaa', J. Sartohadi, D. Mardiatno","doi":"10.23917/forgeo.v35i2.14003","DOIUrl":"https://doi.org/10.23917/forgeo.v35i2.14003","url":null,"abstract":"Some cities in Indonesia which are located on Southern Java Island are susceptible to tsunamis. However, the application of participatory GIS for the assessment of building vulnerability to tsunamis remains rarely evaluated. The aims of this research are 1) to obtain the parameters of building vulnerability to tsunamis using the participatory approach, and 2) to evaluate the results of building vulnerability assessment using participatory GIS. A tsunami inundation map was constructed based on numerical modelling using the Hawke's Bay equation. Participatory approaches were taken to establish the parameters that affect the vulnerability of buildings to tsunamis using in-depth interviews. Respondents were selected using the purposive sampling technique. A geographic information system (GIS) was then applied to build a geodatabase and to perform analysis. The results show that six parameters were obtained from local people’s participation, namely building materials, the number of stories of the buildings , orientation, preservation condition, building row, and natural barriers. All the parameters were identified and interpreted using aerial photos. A field survey was conducted to complete the information on building characteristics. Many buildings near the beach were classified as having high and moderate vulnerability. The main benefit of participatory GIS is that the role of the community makes a significant contribution to providing vulnerability information. It also raises public awareness and improves preparedness for disaster risk management. The drawback is that parameters based on participatory approaches are dynamic and may be different in other areas.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83566989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-20DOI: 10.23917/forgeo.v35i2.13943
B. Harjadi
The reservoir catchment area (RCA) of Mrica in Banjarnegara district is a powerplant in Central Java with a capacity of 184.5 MW. Mrica Dam, also called the dam of Great Commander General Sudirman, has seen its functions gradually decrease due to sedimentation from massive erosion that has occurred in the upland regions. RCA Mrica, with the upland area in Wonosobo district, has an area of 93,546.4 hectares, consisting of six sub-watersheds, Lumajang, Serayu upstream, Begaluh, Serayu, Tulis and Merawu. In 2017, sedimentation in the dam reached 238,236,588.20 m3/year, resulting from an erosion rate of 524,948.33 tons/year. In light of this serious erosion problem in the Mrica RCA, this study aims to estimate the distribution of the erosion level, categorised as slight, moderate and severe, using the SES (soil erosion status) formula. SES was calculated by mapping the level of each influential aspect: aspect, drainage, land cover, slope and soil texture. The calculation used SRTM (Shuttle Radar Topography Mission) satellite imagery and 2017 Landsat TM7 images. The results show slight erosion (50 tons/ha/year) in 1,468.7 ha (1.6%); moderate erosion (50-100 tons/ha/yr) in 56,258.8 ha (60.1%); and severe erosion ( 100 tons/ha/year) in 35,818.9 ha (38.29%). Sampling in the field took into account the slope class of nine classes and was repeated three times, so the number of samples taken in the field was 27. From field visits to the 27 location points, there was conformity in the results of the sensing analysis is much more than 85%”. The results of the erosion calculation using the SES method showed severe erosion of 27.9% (26,137 ha); moderate erosion of 70.2% (65,679 ha); and slight erosion =of 1.8% (1,731 ha). Further erosion calculation using the SES method needs to be compared with calculation using other methods.
{"title":"Erosion Analysis in the Mrica Reservoir Catchment Area in Indonesia using the Soil Erosion Status Method","authors":"B. Harjadi","doi":"10.23917/forgeo.v35i2.13943","DOIUrl":"https://doi.org/10.23917/forgeo.v35i2.13943","url":null,"abstract":"The reservoir catchment area (RCA) of Mrica in Banjarnegara district is a powerplant in Central Java with a capacity of 184.5 MW. Mrica Dam, also called the dam of Great Commander General Sudirman, has seen its functions gradually decrease due to sedimentation from massive erosion that has occurred in the upland regions. RCA Mrica, with the upland area in Wonosobo district, has an area of 93,546.4 hectares, consisting of six sub-watersheds, Lumajang, Serayu upstream, Begaluh, Serayu, Tulis and Merawu. In 2017, sedimentation in the dam reached 238,236,588.20 m3/year, resulting from an erosion rate of 524,948.33 tons/year. In light of this serious erosion problem in the Mrica RCA, this study aims to estimate the distribution of the erosion level, categorised as slight, moderate and severe, using the SES (soil erosion status) formula. SES was calculated by mapping the level of each influential aspect: aspect, drainage, land cover, slope and soil texture. The calculation used SRTM (Shuttle Radar Topography Mission) satellite imagery and 2017 Landsat TM7 images. The results show slight erosion (50 tons/ha/year) in 1,468.7 ha (1.6%); moderate erosion (50-100 tons/ha/yr) in 56,258.8 ha (60.1%); and severe erosion ( 100 tons/ha/year) in 35,818.9 ha (38.29%). Sampling in the field took into account the slope class of nine classes and was repeated three times, so the number of samples taken in the field was 27. From field visits to the 27 location points, there was conformity in the results of the sensing analysis is much more than 85%”. The results of the erosion calculation using the SES method showed severe erosion of 27.9% (26,137 ha); moderate erosion of 70.2% (65,679 ha); and slight erosion =of 1.8% (1,731 ha). Further erosion calculation using the SES method needs to be compared with calculation using other methods.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84242047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-08DOI: 10.23917/forgeo.v35i1.13356
Ulfa Azhari Shabira, S. Giyarsih
In 2016, various settlements in Garut Regency, notably Garut Kota Sub-District, located along the Cimanuk River, were affected by a flash flood. As a result, many residents relocated to other places, far from the city. This research was conducted in three residential relocation areas: Gadok Housing, Kopi Lombang Housing and Cisereuh Housing. The purpose of the study is to determine the adaptation strategies of relocating communities. The research was conducted using mixed-methods techniques with descriptive quantitative and qualitative data analysis. The results are shown in the adaptation strategies of the affected communities and demonstrate that the relocated communities living in new settlements pursued adaptation strategies such as adjustment and adaptation with reaction. Adaptation by adjustment was carried out by accepting the post-relocation situation and taking up jobs in different sectors. Meanwhile, adaptation by reaction entailed making changes to the physical form of buildings, planting mixed gardens or constructing pet cages in the yard. Relocating residents often lacked the motivation to move to alternative shelters due to financial inability and a sense of comfort in their new settlement.
{"title":"The Adaptation Strategy of Flash Flood Victims in Urban Areas, Garut Kota Sub-District","authors":"Ulfa Azhari Shabira, S. Giyarsih","doi":"10.23917/forgeo.v35i1.13356","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.13356","url":null,"abstract":"In 2016, various settlements in Garut Regency, notably Garut Kota Sub-District, located along the Cimanuk River, were affected by a flash flood. As a result, many residents relocated to other places, far from the city. This research was conducted in three residential relocation areas: Gadok Housing, Kopi Lombang Housing and Cisereuh Housing. The purpose of the study is to determine the adaptation strategies of relocating communities. The research was conducted using mixed-methods techniques with descriptive quantitative and qualitative data analysis. The results are shown in the adaptation strategies of the affected communities and demonstrate that the relocated communities living in new settlements pursued adaptation strategies such as adjustment and adaptation with reaction. Adaptation by adjustment was carried out by accepting the post-relocation situation and taking up jobs in different sectors. Meanwhile, adaptation by reaction entailed making changes to the physical form of buildings, planting mixed gardens or constructing pet cages in the yard. Relocating residents often lacked the motivation to move to alternative shelters due to financial inability and a sense of comfort in their new settlement.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85453191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-10DOI: 10.23917/forgeo.v35i1.13507
R. Prastowo, H. Helmi, O. Trianda, R. Umam
In the last five years, the need for materials to build infrastructure in Kulon Progo Regency has increased with the construction of an international airport. In the construction process, strong earth or rock materials are needed to make buildings resistant to earthquakes, one of which is andesite rock. This study aims to determine andesite rocks' resources using a three-dimensional model based on the value of resistivity in Kalirejo district Kokap Kulon Progo. The research was conducted by geological and geophysical survey. Based on data on the distribution of rocks in the research area included in the intermediate igneous rocks, andesite. These rocks are intrusions that develop in research areas. Petrography analysis is used to determine the types of minerals in andesite rocks and determine which levels of rock changes have changed or not to affect the strength of rocks. These rocks are intrusions that develop in research areas. Geophysical survey is by resistivity method using configuration dipole-dipole with five lines, and each stretch is 200 m. Based on three-dimensional model resistivity, fresh andesite is at a depth of between 5-10 m. Value of andesite resistivity is more than 668 Ωm, while the value of weathered andesite resistivity ranges from 256-536 Ωm and andesite resources about 332,580 tons.
{"title":"Identification of Andesite Resource Potential In Kalirejo Area, Kokap Sub-District, Kulon Progo Using Resistivity Method","authors":"R. Prastowo, H. Helmi, O. Trianda, R. Umam","doi":"10.23917/forgeo.v35i1.13507","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.13507","url":null,"abstract":"In the last five years, the need for materials to build infrastructure in Kulon Progo Regency has increased with the construction of an international airport. In the construction process, strong earth or rock materials are needed to make buildings resistant to earthquakes, one of which is andesite rock. This study aims to determine andesite rocks' resources using a three-dimensional model based on the value of resistivity in Kalirejo district Kokap Kulon Progo. The research was conducted by geological and geophysical survey. Based on data on the distribution of rocks in the research area included in the intermediate igneous rocks, andesite. These rocks are intrusions that develop in research areas. Petrography analysis is used to determine the types of minerals in andesite rocks and determine which levels of rock changes have changed or not to affect the strength of rocks. These rocks are intrusions that develop in research areas. Geophysical survey is by resistivity method using configuration dipole-dipole with five lines, and each stretch is 200 m. Based on three-dimensional model resistivity, fresh andesite is at a depth of between 5-10 m. Value of andesite resistivity is more than 668 Ωm, while the value of weathered andesite resistivity ranges from 256-536 Ωm and andesite resources about 332,580 tons.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85235058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-10DOI: 10.23917/forgeo.v35i1.12270
Maryadi Budi Wiyono, T. Adji
Pasaran is the only productive small island functioning as the anchovy and green clam production center in Bandar Lampung. Its water use has, however, increased since its designation as an economically fishery-based development area or minapolitan in 2012. This is due to the fact that groundwater resources in small island ecosystems surrounded by seawaters with a narrow diameter are easily affected by the insistence of seawater. Moreover, population pressure and land-use change are also feared to be affecting groundwater quality. Therefore, this research was conducted to analyze and evaluate groundwater resource quality in Pasaran Island using five wells on the entire island as sampling points selected based on census. The samples were tested for physical, chemical, and biological parameters in the laboratory and compared with water quality standards (Minister of Health’s Regulation No. 32/2007). The results showed relatively low water quality because the samples contained up to 3900 μS/cm salinity, 3771.9 mg/l chlorides, 31.7–141.52 mg/l nitrates, and 6.8–170 MPN/100ml total coliform which exceed the standards for drinking water. Meanwhile, wells 1, 4, and 5 were found to be safe for sanitation-hygiene purposes and well 1 was suitable for public baths even though they are not of drinking quality. This means the groundwater quality generally met Class II-water requirements for clean water supplies.
{"title":"Analysis of Groundwater Quality for Clean Water Supply in Pasaran Island, Bandar Lampung City, Indonesia","authors":"Maryadi Budi Wiyono, T. Adji","doi":"10.23917/forgeo.v35i1.12270","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.12270","url":null,"abstract":"Pasaran is the only productive small island functioning as the anchovy and green clam production center in Bandar Lampung. Its water use has, however, increased since its designation as an economically fishery-based development area or minapolitan in 2012. This is due to the fact that groundwater resources in small island ecosystems surrounded by seawaters with a narrow diameter are easily affected by the insistence of seawater. Moreover, population pressure and land-use change are also feared to be affecting groundwater quality. Therefore, this research was conducted to analyze and evaluate groundwater resource quality in Pasaran Island using five wells on the entire island as sampling points selected based on census. The samples were tested for physical, chemical, and biological parameters in the laboratory and compared with water quality standards (Minister of Health’s Regulation No. 32/2007). The results showed relatively low water quality because the samples contained up to 3900 μS/cm salinity, 3771.9 mg/l chlorides, 31.7–141.52 mg/l nitrates, and 6.8–170 MPN/100ml total coliform which exceed the standards for drinking water. Meanwhile, wells 1, 4, and 5 were found to be safe for sanitation-hygiene purposes and well 1 was suitable for public baths even though they are not of drinking quality. This means the groundwater quality generally met Class II-water requirements for clean water supplies.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74445530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-10DOI: 10.23917/forgeo.v35i1.11782
A. Purwanto, U. J. Wisha, Erick Karno Hutomo
Saleh Bay is a semi-enclosed area of water in Nusa Tenggara Barat Province that is enriched by fisheries resources. The bay’s strategic position, surrounded by several small islands, makes it an area of fertile water. An area of water is considered a potentially ideal fishing ground if it contains several oceanographic phenomena, including thermal fronts and upwelling. Fishing activities in Saleh Bay have been found to be ineffective and inefficient due to local people’s continued use of traditional methods such as fishing by signs of nature (instincts), wind direction, astrological signs and previous experience. This study aimed to create a mapping model of the fishing grounds in Saleh Bay based on remote sensing satellite data. Spatial analysis of daily level 3 images from the Suomi-National Polar-Orbiting Partnership (SNPP) was conducted throughout January and August 2019. The image acquisition period was adapted based on the seasonal system of Indonesia. The study area was determined based on thermal front events as identified by sea surface temperature (SST) data analysed using statistical regression with a Non-Linear Multi-Channel SST (NLSST) approach. An ideal fishing ground is characterised by several oceanographic settings such as upwelling and thermal front occurrence. The average SST distribution in January 2019 was relatively high, ranging from 30.39 to 33.70 oC, while in August 2019, the temperature declined significantly, ranging from 25.09 to 29.30 oC. Concerning the fishing ground model, a plethora of potential fishing ground areas were identified in August compared to January 2019, at 144 and 42 points respectively. This reflected the density of the fishing grounds observed. The fishing grounds were most likely to be concentrated in the bay mouth during the southwest monsoon and within the bay near the plateau during the northeast monsoon. The seasonal variability of Saleh Bay played a significant role in the spatial extraction of the fishing ground data.
{"title":"Fishing Ground Mapping Model in The Semi-Enclosed Saleh Bay, West Nusa Tenggara","authors":"A. Purwanto, U. J. Wisha, Erick Karno Hutomo","doi":"10.23917/forgeo.v35i1.11782","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.11782","url":null,"abstract":"Saleh Bay is a semi-enclosed area of water in Nusa Tenggara Barat Province that is enriched by fisheries resources. The bay’s strategic position, surrounded by several small islands, makes it an area of fertile water. An area of water is considered a potentially ideal fishing ground if it contains several oceanographic phenomena, including thermal fronts and upwelling. Fishing activities in Saleh Bay have been found to be ineffective and inefficient due to local people’s continued use of traditional methods such as fishing by signs of nature (instincts), wind direction, astrological signs and previous experience. This study aimed to create a mapping model of the fishing grounds in Saleh Bay based on remote sensing satellite data. Spatial analysis of daily level 3 images from the Suomi-National Polar-Orbiting Partnership (SNPP) was conducted throughout January and August 2019. The image acquisition period was adapted based on the seasonal system of Indonesia. The study area was determined based on thermal front events as identified by sea surface temperature (SST) data analysed using statistical regression with a Non-Linear Multi-Channel SST (NLSST) approach. An ideal fishing ground is characterised by several oceanographic settings such as upwelling and thermal front occurrence. The average SST distribution in January 2019 was relatively high, ranging from 30.39 to 33.70 oC, while in August 2019, the temperature declined significantly, ranging from 25.09 to 29.30 oC. Concerning the fishing ground model, a plethora of potential fishing ground areas were identified in August compared to January 2019, at 144 and 42 points respectively. This reflected the density of the fishing grounds observed. The fishing grounds were most likely to be concentrated in the bay mouth during the southwest monsoon and within the bay near the plateau during the northeast monsoon. The seasonal variability of Saleh Bay played a significant role in the spatial extraction of the fishing ground data.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79458428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-10DOI: 10.23917/forgeo.v35i1.13007
A. Wicaksono, N. M. Farda, N. Khakhim, T. W. Wibowo
Photos shared by social media users act as an approach in identifying tourist activity. Popular tourist attractions are judged based on the large number of photos or high photo density. In Bantul Regency, Indonesia, beaches have diverse attractions which tourists can enjoy and immortalize through photos. Analyzing the contents of photos on Flickr provides information on the type(s) of beaches or coastal attractions preferred by tourists. This study examined the availability of geotagged Flickr photos to assist in making relevant beach tourism management policies. It employed pattern analysis with the average nearest neighbor, density analysis with kernel density estimation, image content analysis with tourist attraction as the variable, and overlay analysis to formulate recommendations for beach tourism management based on the popularity level of the attractions. The results indicate that each of the local beaches offers different attractions with varying popularity levels and that natural beauty is the main feature attracting tourists to visit all beaches, except Baros. Based on the pattern analysis, the Flickr photos are clustered on several beaches of high popularity, such as Parangtritis, Baros, Depok, and Cemara Sewu. By using geotagged Flickr photo data and refers to the concept of tourism supply and demand, recommendations for developing the attractive features on these beaches have been compiled according to their respective themes and popularity levels to target specific tourist market segments and design integrated tour or travel packages.
{"title":"Flickr Photos Analysis for Beach Tourism Management in Bantul Regency, Indonesia: Popularity and Tourist Attractions","authors":"A. Wicaksono, N. M. Farda, N. Khakhim, T. W. Wibowo","doi":"10.23917/forgeo.v35i1.13007","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.13007","url":null,"abstract":"Photos shared by social media users act as an approach in identifying tourist activity. Popular tourist attractions are judged based on the large number of photos or high photo density. In Bantul Regency, Indonesia, beaches have diverse attractions which tourists can enjoy and immortalize through photos. Analyzing the contents of photos on Flickr provides information on the type(s) of beaches or coastal attractions preferred by tourists. This study examined the availability of geotagged Flickr photos to assist in making relevant beach tourism management policies. It employed pattern analysis with the average nearest neighbor, density analysis with kernel density estimation, image content analysis with tourist attraction as the variable, and overlay analysis to formulate recommendations for beach tourism management based on the popularity level of the attractions. The results indicate that each of the local beaches offers different attractions with varying popularity levels and that natural beauty is the main feature attracting tourists to visit all beaches, except Baros. Based on the pattern analysis, the Flickr photos are clustered on several beaches of high popularity, such as Parangtritis, Baros, Depok, and Cemara Sewu. By using geotagged Flickr photo data and refers to the concept of tourism supply and demand, recommendations for developing the attractive features on these beaches have been compiled according to their respective themes and popularity levels to target specific tourist market segments and design integrated tour or travel packages.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81237049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-10DOI: 10.23917/forgeo.v35i1.11510
K. Khairunnisa, Y. Abubakar, Didik Sugianto
Akbar, A., Ma'rif, S. (2014). Arah Perkembangan Kawasan Perumahan Pasca Bencana Tsunami di Kota Banda Aceh. Teknik PWK (Perencanaan Wilayah Kota), 3(2), 274-284.Bandrova, T., Zlatanova, S., Konecny, M. (2012). Three-dimensional maps for disaster management. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume I-2, XXII ISPRS Congress, August-September 2012, pp. 19-24. International Society for Photogrammetry and Remote Sensing.BNPB. (2012). Menuju Indonesia Tangguh Tsunami. Jakarta: Badan Nasional Penanggulangan Bencana.BNPB. (2016). Kebijakan dan Strategi Penanggulangan Bencana 2015-2019 (Jakstra PB).BPBA. (2015). Kajian Risiko Bencana Aceh 2016-2020.BPBD. (2017). Rencana Pengurangan Bencana. Banda Aceh.BRR. (2005). Program Blueprint Aceh.Carreño, M. L., Cardona, O. D., Barbat, A. H. (2007). A Disaster Risk Management Performance Index. Natural Hazards, 41(1), 1-20.Danugroho, A., Umamah, N., Pratama, A. R. (2020). Aceh Tsunami and Government Policy in Handling It: A Historical Study. In IOP Conference Series: Earth and Environmental Science (Vol. 485, No. 1, p. 012140). IOP Publishing.Febriana, D. S., Abubakar, Y. (2015). Kesiapsiagaan Masyarakat Desa Siaga Bencana dalam Menghadapi Bencana Gempa Bumi di Kecamatan Meuraxa Kota Banda Aceh. Jurnal Ilmu Kebencanaan: Program Pascasarjana Unsyiah, 2(3).Gadeng, A. N., Furqan, M. H. (2019). The Development of Settlement in the Tsunami Red Zone Area of Banda Aceh City. KnE Social Sciences, 1-13.Godschalk, D., Bohl, C. C., Beatley, T., Berke, P., Brower, D., Kaiser, E. J. (1999). Natural Hazard Mitigation: Recasting Disaster Policy and Planning. Island press.Goltz, J., Yamori, K. (2020). Tsunami Preparedness and Mitigation Strategies. In Oxford Research Encyclopedia of Natural Hazard Science.Herrmann, G. (2013). Regulation of Coastal Zones and Natural Disasters: Mitigating the Impact of Tsunamis in Chile Through Urban and Regional Planning. Issues in Legal Scholarship, 11(1), 29-44.Jain, Garima., Singh, Chandni and Malani, T. (2017). Rethinking Post-disaster Relocation in Urban India. International Institute for Environment and Development.Kafle, S. K. (2006). Rapid Disaster Risk Assessment of Coastal Communities: A Case Study of Mutiara Village, Banda Aceh, Indonesia. In Proceedings of the International Conference on Environment and Disaster Management Held in Jakarta, Indonesia on December (pp. 5-8).Mardiatno, D., Malawani, M. N., Annisa, D. N., Wacano, D. (2017). Review on Tsunami Risk Reduction in Indonesia Based on Coastal and Settlement Typology. The Indonesian Journal of Geography, 49(2), 186-197.Marlyono, S. G. (2017). Peranan Literasi Informasi Bencana terhadap Kesiapsiagaan Bencana Masyarakat Jawa Barat. Jurnal Geografi Gea, 16(2), 116-123.Oktari, R. S., Nugroho, A., Fahmi, M., Suppasri, A., Munadi, K., Amra, R. (2021). Fifteen years of the 2004 Indian Ocean Tsunami in Aceh-Indonesia: Mitigation, preparedness and challenges for a long-term disaster recov
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{"title":"Do Disaster Literacy and Mitigation Policy Affect Residents Resettling in Tsunami Prone Areas? Study from the City of Banda Aceh, Indonesia","authors":"K. Khairunnisa, Y. Abubakar, Didik Sugianto","doi":"10.23917/forgeo.v35i1.11510","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.11510","url":null,"abstract":"Akbar, A., Ma'rif, S. (2014). Arah Perkembangan Kawasan Perumahan Pasca Bencana Tsunami di Kota Banda Aceh. Teknik PWK (Perencanaan Wilayah Kota), 3(2), 274-284.Bandrova, T., Zlatanova, S., Konecny, M. (2012). Three-dimensional maps for disaster management. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume I-2, XXII ISPRS Congress, August-September 2012, pp. 19-24. International Society for Photogrammetry and Remote Sensing.BNPB. (2012). Menuju Indonesia Tangguh Tsunami. Jakarta: Badan Nasional Penanggulangan Bencana.BNPB. (2016). Kebijakan dan Strategi Penanggulangan Bencana 2015-2019 (Jakstra PB).BPBA. (2015). Kajian Risiko Bencana Aceh 2016-2020.BPBD. (2017). Rencana Pengurangan Bencana. Banda Aceh.BRR. (2005). Program Blueprint Aceh.Carreño, M. L., Cardona, O. D., Barbat, A. H. (2007). A Disaster Risk Management Performance Index. Natural Hazards, 41(1), 1-20.Danugroho, A., Umamah, N., Pratama, A. R. (2020). Aceh Tsunami and Government Policy in Handling It: A Historical Study. In IOP Conference Series: Earth and Environmental Science (Vol. 485, No. 1, p. 012140). IOP Publishing.Febriana, D. S., Abubakar, Y. (2015). Kesiapsiagaan Masyarakat Desa Siaga Bencana dalam Menghadapi Bencana Gempa Bumi di Kecamatan Meuraxa Kota Banda Aceh. Jurnal Ilmu Kebencanaan: Program Pascasarjana Unsyiah, 2(3).Gadeng, A. N., Furqan, M. H. (2019). The Development of Settlement in the Tsunami Red Zone Area of Banda Aceh City. KnE Social Sciences, 1-13.Godschalk, D., Bohl, C. C., Beatley, T., Berke, P., Brower, D., Kaiser, E. J. (1999). Natural Hazard Mitigation: Recasting Disaster Policy and Planning. Island press.Goltz, J., Yamori, K. (2020). Tsunami Preparedness and Mitigation Strategies. In Oxford Research Encyclopedia of Natural Hazard Science.Herrmann, G. (2013). Regulation of Coastal Zones and Natural Disasters: Mitigating the Impact of Tsunamis in Chile Through Urban and Regional Planning. Issues in Legal Scholarship, 11(1), 29-44.Jain, Garima., Singh, Chandni and Malani, T. (2017). Rethinking Post-disaster Relocation in Urban India. International Institute for Environment and Development.Kafle, S. K. (2006). Rapid Disaster Risk Assessment of Coastal Communities: A Case Study of Mutiara Village, Banda Aceh, Indonesia. In Proceedings of the International Conference on Environment and Disaster Management Held in Jakarta, Indonesia on December (pp. 5-8).Mardiatno, D., Malawani, M. N., Annisa, D. N., Wacano, D. (2017). Review on Tsunami Risk Reduction in Indonesia Based on Coastal and Settlement Typology. The Indonesian Journal of Geography, 49(2), 186-197.Marlyono, S. G. (2017). Peranan Literasi Informasi Bencana terhadap Kesiapsiagaan Bencana Masyarakat Jawa Barat. Jurnal Geografi Gea, 16(2), 116-123.Oktari, R. S., Nugroho, A., Fahmi, M., Suppasri, A., Munadi, K., Amra, R. (2021). Fifteen years of the 2004 Indian Ocean Tsunami in Aceh-Indonesia: Mitigation, preparedness and challenges for a long-term disaster recov","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82775734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-07DOI: 10.23917/forgeo.v35i1.12325
M. F. Ghazali, A. Tridawati, Mamad Sugandi, Aqilla Fitdhea Anesta, K. Wikantika
COVID-19 is currently the hot topic of discussion by scientists because of its ability to quickly spread, in line with everyday human activities. One of the environmental factors related to climatic parameters, such as the air temperature, contributed to the spreading of COVID-19 in the last four months. Its distribution ability is no longer local as it successfully halts the important activities in many countries globally. This study aims to explain the opportunity of geospatial analysis in handling the COVID-19 distribution locally based on the characteristics of demographic data. Various data, including the confirmed positive for COVID-19, age-based population, and Landsat 8 satellite imagery data were used to determine the spatial characteristics of the COVID-19 distribution per September 2020 in Bandung, Indonesia. An inverse distance weighted (IDW), Moran's I index and local indicator spatial association (LISA), and a proposed ratio of the elderly population against the population with confirmed positive for COVID-19 (CoVE) were used as the approach to determine its distribution characteristics. The information derived from Landsat 8 satellite imagery, such as the residential area, surface temperature, and humidity based on the supervised classification, land surface temperature (LST), and the normalized difference water index (NDWI) was used to perform the analysis. The results showed that the positive population of COVID-19 was concentrated in Bandung city. However, with a Moran's I value of 0.316, not all are grouped into the same category. There are only 8, 2, 5, and 3 districts categorized as HH, HL, LL, and LH. However, the areas with a large or small number of elderlies do not always correlate with the high number of confirmed positives for COVID-19. There are only 3, 1, and 3 districts classified as HH, HL, and LL. They were represented by the values of Moran's I, for about 0.057. The positive relationship between confirmed positive for COVID-19 and the built-up area, surface temperature, humidity, and the elderly population based on the coefficient of determination (R2) were 0.03, 0.28, 0.25, and 0.019, respectively. The study also shows that the vulnerability of those areas is relatively low. The study shows that the vulnerabilities in these areas are relatively low and the recommendation for COVID-19 widespread mitigation has to consider the demographic characteristics precisely in the large scale social restrictions (LSSR).
{"title":"Spatial Analysis to Mitigate the Spread of Covid-19 Based on Regional Demographic Characteristics","authors":"M. F. Ghazali, A. Tridawati, Mamad Sugandi, Aqilla Fitdhea Anesta, K. Wikantika","doi":"10.23917/forgeo.v35i1.12325","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.12325","url":null,"abstract":"COVID-19 is currently the hot topic of discussion by scientists because of its ability to quickly spread, in line with everyday human activities. One of the environmental factors related to climatic parameters, such as the air temperature, contributed to the spreading of COVID-19 in the last four months. Its distribution ability is no longer local as it successfully halts the important activities in many countries globally. This study aims to explain the opportunity of geospatial analysis in handling the COVID-19 distribution locally based on the characteristics of demographic data. Various data, including the confirmed positive for COVID-19, age-based population, and Landsat 8 satellite imagery data were used to determine the spatial characteristics of the COVID-19 distribution per September 2020 in Bandung, Indonesia. An inverse distance weighted (IDW), Moran's I index and local indicator spatial association (LISA), and a proposed ratio of the elderly population against the population with confirmed positive for COVID-19 (CoVE) were used as the approach to determine its distribution characteristics. The information derived from Landsat 8 satellite imagery, such as the residential area, surface temperature, and humidity based on the supervised classification, land surface temperature (LST), and the normalized difference water index (NDWI) was used to perform the analysis. The results showed that the positive population of COVID-19 was concentrated in Bandung city. However, with a Moran's I value of 0.316, not all are grouped into the same category. There are only 8, 2, 5, and 3 districts categorized as HH, HL, LL, and LH. However, the areas with a large or small number of elderlies do not always correlate with the high number of confirmed positives for COVID-19. There are only 3, 1, and 3 districts classified as HH, HL, and LL. They were represented by the values of Moran's I, for about 0.057. The positive relationship between confirmed positive for COVID-19 and the built-up area, surface temperature, humidity, and the elderly population based on the coefficient of determination (R2) were 0.03, 0.28, 0.25, and 0.019, respectively. The study also shows that the vulnerability of those areas is relatively low. The study shows that the vulnerabilities in these areas are relatively low and the recommendation for COVID-19 widespread mitigation has to consider the demographic characteristics precisely in the large scale social restrictions (LSSR).","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89699723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.23917/forgeo.v35i1.12273
A. Yudono, J. Purnomo, Ratnaningsih Damayanti
Stunting has become a global concern. The incidence of stunting in the world contributes to 15% of under-five mortality, with 55 million children losing their health, and it is estimated to reduce the country's GDP level by up to 7%. In Indonesia, the incidence of stunting has become one of the main health problems that need to be solved immediately. Malang Regency is one of the districts in East Java Province that has received the spotlight regarding this problem. This research examined the risk factors of stunting in Malang Regency through Geographically Weighted Regression (GWR). GWR was carried out to calculate the correlation between predetermined demographic, health, and economic variables, which were assumed to influence risk factors of stunting. GWR allocation and model examinations are important in understanding risk factors of stunting in the study of disease transmission in the investigation zone. Based on GWR analysis, the research shows that only four (4) sub-variables were significant: the number of poor people, level of education, number of health facilities, and access to health facilities. We also found that Lawang, Gondanglegi, and Turen districts have high-risk areas to stunting. Therefore, within this study that correlates to government policy to decrease or eliminate stunting incidents, districts belonging to the high-risk class should be prioritized or concerned. Moreover, based on LISA, some districts are affected by the risk factors of stunting from the surrounding districts with higher stunting potential value such as Gondanglegi and Pagelaran Districts.
{"title":"Geographical Weighted Regression of Risk Factor of Stunting in Malang Regency, Indonesia","authors":"A. Yudono, J. Purnomo, Ratnaningsih Damayanti","doi":"10.23917/forgeo.v35i1.12273","DOIUrl":"https://doi.org/10.23917/forgeo.v35i1.12273","url":null,"abstract":"Stunting has become a global concern. The incidence of stunting in the world contributes to 15% of under-five mortality, with 55 million children losing their health, and it is estimated to reduce the country's GDP level by up to 7%. In Indonesia, the incidence of stunting has become one of the main health problems that need to be solved immediately. Malang Regency is one of the districts in East Java Province that has received the spotlight regarding this problem. This research examined the risk factors of stunting in Malang Regency through Geographically Weighted Regression (GWR). GWR was carried out to calculate the correlation between predetermined demographic, health, and economic variables, which were assumed to influence risk factors of stunting. GWR allocation and model examinations are important in understanding risk factors of stunting in the study of disease transmission in the investigation zone. Based on GWR analysis, the research shows that only four (4) sub-variables were significant: the number of poor people, level of education, number of health facilities, and access to health facilities. We also found that Lawang, Gondanglegi, and Turen districts have high-risk areas to stunting. Therefore, within this study that correlates to government policy to decrease or eliminate stunting incidents, districts belonging to the high-risk class should be prioritized or concerned. Moreover, based on LISA, some districts are affected by the risk factors of stunting from the surrounding districts with higher stunting potential value such as Gondanglegi and Pagelaran Districts.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89787487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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