The Adaptation Strategy of Flash Flood Victims in Urban Areas, Garut Kota Sub-District

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.

Fishing Ground Mapping Model in The Semi-Enclosed Saleh Bay, West Nusa Tenggara

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.

Flickr Photos Analysis for Beach Tourism Management in Bantul Regency, Indonesia: Popularity and Tourist Attractions

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.

Identification of Andesite Resource Potential In Kalirejo Area, Kokap Sub-District, Kulon Progo Using Resistivity Method

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.

Do Disaster Literacy and Mitigation Policy Affect Residents Resettling in Tsunami Prone Areas? Study from the City of Banda Aceh, Indonesia

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Analysis of Groundwater Quality for Clean Water Supply in Pasaran Island, Bandar Lampung City, Indonesia

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.

Spatial Analysis to Mitigate the Spread of Covid-19 Based on Regional Demographic Characteristics

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).

Spatial Analysis on Tsunami Predictions in Pandeglang Regency

Pandeglang Regency is an area that has the potentiel to be hit by tsunamis. The plate subduction paths of Indo-Australia and Anak Krakatau Volcano make Pandeglang Regency a region with a high tsunami potential. One step that can be taken to overcome and minimize losses is to do spatial planning to protect it against potential tsunami damage. This research aimed to evaluate the spatial area of Pandeglang Regency based on the identification of potential tsunami hazards. The concept of modelling the tsunami inundation height developed by Berryman and based on Head Regulation No.4 of 2012 of the Indonesian National Board for Disaster Management has been used to identify potential tsunami hazards. The modelling was carried out by calculating the potential distribution of tsunami wave heights in coastal areas. Three scenarios were used to estimate the distribution. The results showed that the first scenario predicted a maximum tsunami height of 7.5 meters above sea level with the furthest tsunami inundation reaching 1,700.12 meters. Second scenario predicted maximum height of 15 meters, with the furthest tsunami inundation reaching 3,384.62 meters. Meanwhile, the last scenario was able to predict a height of 20 meters and showed the furthest tsunami inundation reaching 5.155,11 meters. These results proved that in all scenarios, the widest inundation would occur in Panimbang Regency. This is due to the relatively small variations in roughness and slope of the surface. The same condition also occurs in the last two scenarios, in which Sumur District was the area most ffected. Therefore, the spatial plan of Pandeglang Regency needs to be evaluated and the function of residential area changed to reduce and prevent large losses.

Geographical Weighted Regression of Risk Factor of Stunting in Malang Regency, Indonesia

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.

Utilizing Vulnerability and Risk Indexes for Cultural Heritage in Yogyakarta and Central Java

Indonesia is home to many cultural heritages which are exposed to natural disaster, its number has grown by 400% within the years of 1975-2010. In order to protect the cultural heritages, the national government released InaRisk – a web based geospatial data to identify risk information. This application, however, not fully apprises its users of the potential loss that cultural heritage objects, especially temples, may sustain. For these reasons, the research set out to evaluate the potential loss of temples by making use of disaster vulnerability and risk approaches. Seven temples were exposed to earthquake and landslide hazards; hence, observed as the research object on a micro-scale. The research method combined tabular, spatial, and temporal data of several indicators, namely types of building materials, building’s structural integrity after earthquakes and landslides, the number of salvageable objects, building age, significance, historical value, and the number of visitors. The results showed that Prambanan and Sewu Temples had the most substantial amounts of potential losses incurred from damages to at-risk elements, namely the numbers of visitors, employees, and supporting facilities and their distances to sources of hazards. Assessing the numerical values of losses requires further improvements in accuracy as it has not thoroughly factored in the significance of the temples, which is composed of historical value, building age, number of visitors, and other components. Valuation of this significance is still limited to currently available data, including the price of the constituent rocks, area and volume, and supporting facilities.