RENCANA STRATEGIS PENENTUAN ALTERNATIF RUMAH SAKIT RUJUKAN COVID-19: Studi Kasus Kabupaten Bogor

oai:ojs2.localhost:8081:article/16Beberapa wilayah di Kab. Bogor merupakan daerah penyangga Ibukota negara, dengan kepadatan penduduk tinggi dan merupakan pusat perekonomian. Akibatnya, wilayah tersebut terancam mempunyai kerentanan yang tinggi terhadap penyebaran COVID-19. Peningkatan pasien terkonfirmasi positif COVID-19 di Kab. Bogor semakin masif dari hari ke hari. Peningkatan kasus yang signifikan ini sangat mengkhawatirkan, terutama terhadap kemampuan fasilitas pelayanan kesehatan. Kemampuan fasilitas pelayan kesehatan, terutama rumah sakit rujukan untuk menjangkau wilayah-wilayah rentan kasus positif dapat dengan mudah dilihat menggunakan analisis spasial. Tujuan dari penelitian ini adalah menentukan lokasi strategis fasilitas kesehatan di Kab. Bogor sebagai Rumah Sakit rujukan COVID-19 dengan menggunakan metode analisis jaringan. Rencana strategis rumah sakit rujukan ditentukan berdasarkan wilayah-wilayah yang tidak bisa dijangkau oleh rumah sakit yang ada. Selanjutnya, penentuan indeks kesiapan rumah sakit rujukan menggunakan analisis multi kriteria Simple Additive Weighting. Hasil penelitian menunjukkan bahwa terdapat satu rumah sakit existing dengan indeks kesiapan tinggi, kemudian 4 rumah sakit dengan indeks kesiapan sedang. Lebih lanjut, terdapat 13 alternatif rumah sakit rujukan menunjukkan kesiapan rendah. Sebaran rumah sakit di Kab. Bogor pun tidak banyak, dan hanya memusat di bagian tengah wilayah Kab. Bogor. Oleh karena itu, seluruh rumah sakit alternatif sangat strategis menjadi rumah sakit rujukan COVID-19. Jumlah rumah sakit rujukan COVID-19 di Kab. Bogor masih kurang menjangkau seluruh wilayah, sehingga pemerintah daerah selayaknya berupaya untuk melakukan penambahan jumlah rumah sakit atau penambahan kapasitas layanan kesehatan

Spatial analysis of selected biodiversity features in protected areas: a case study in Tuscany region

The development of strategies for biodiversity analysis is critical at several levels, particularly at the national one. The World Conference on Biological Diversity held in Rio de Janeiro in 1992, the European Natura 2000 network and the Environmental Conference of the Regions of Europe (EN.CO.RE) brought forward several measures aiming at the preservation of Biodiversity. Targets for biodiversity preservation include protected areas among others. Accordingly, the analysis of the degree of biodiversity of protected areas proves to be a valid tool to evaluate the effectiveness of those measures. The present manuscript analyses the degree of some relevant features of biodiversity in the Region of Tuscany, through the implementation of multidimensional indicators in a Spatial MultiCriteria Analysis. After a state of the art of biodiversity definition, four indicators have been used for the analysis. A raster map in which pixels have higher or lower values of biodiversity was produced in order to investigate which of these values might be located in protected areas. Protected areas with high value of biodiversity confirmed that the adopted environmental policies are positively related to the conservation of biodiversity. The result of the analysis, corroborated through auto-correlational statistical analysis, has highlighted the important role of protected areas in maintaining a certain degree of biodiversity

GIS-Based Local Ordered Weighted Averaging: A Case Study in London, Ontario

GIS-based multicriteria analysis is a procedure for combining a set of criterion maps and associated criterion weights to obtain overall value for each spatial unit (location) in the study area. Ordered Weighted Averaging (OWA) is a generic algorithm of the multicriteria analysis. It has been integrated into GIS and applied for tackling a wide range of spatial problems. However, the conventional OWA method is based on an assumption of spatial homogeneity of its parameters. Therefore, it is referred to as a global model. This thesis proposes a local form OWA. The local model is based on the range sensitivity principle. A case study of examining spatial patterns of socioeconomic status in London, Ontario is presented. The results show that there are substantial differences between the spatial patterns generated by the global and local OWA methods

Potential nuclear power plant sites selection using multicriteria decision analysis

Strategic decision-making is very difficult, particularly when multicriteria are involved. Multi-Criteria Decision Analysis (MCDA) method is an important approach that is applied to many complex decisions-makings. MCDA has been combined with Geographical Information System (GIS) to tackle spatial decision-making problems. One of the hardest spatial decision-making problems is the Nuclear Power Plant sites selection (NPP siting). This study has developed hybrid GIS and MCDA models to conduct NPP siting. Saudi Arabia was chosen to be the case study for this research. The identification of NPP siting area was divided into two phases. Phase I was a survey of all potential suitable areas for siting NPPs in the country. Phase II was a suggestion and ranking of the preferable suitable NPPs sites. The spatial analysis software ArcGIS 10.6 was utilized throughout this study. Thirteen significant criteria were applied to screen out unsuitable areas for siting NPPs. The results of phase I revealed that a scarcity of water in Saudi Arabia was the major reason to discard 96% of the possible sites. Furthermore, the overlaying process of all these criteria could dispose of nearly 98% of the contiguous Saudi lands. The remaining 2% land area was discerned to be suitable for positioning NPPs, which covered an area of 21473 km2 and 13395 km2 on the western and eastern coast, respectively. Meanwhile, the survey revealed that sea-level rise sensitivity must be considered on the eastern coast for the safe operation of NPPs. Further analyses disclosed that a sea-level rise of 2 meters could reduce the possible land areas by 20% and 13% in the eastern and western coastal areas correspondingly. The net feasible areas were inversely proportional to the aggregation of suitable lands into specific NPP footprint. It was concluded that the proposed assembly strategy could reduce the net effective area on the western coast for siting NPPs such as SMR350 (small reactor), AP1000 (moderate reactor) and EPR1600 (large reactor) by almost 22%, 37%, and 47%, respectively. The results of phase II (identification and ranking process) revealed that there are many locations available for siting NPPs in Saudi Arabia. Since the first-option areas, whose suitability scored 9/10, would be more than enough for proposing reasonable number of NPP sites on both coastal areas, the other options of ranked areas 2, 3, 4 and 5 (whose suitability were 8, 7, 6 and 5 respectively) were ignored for this time. There were 20 proposed NPP sites; 11 of which were on the western, and the other 9 on the eastern coast. Both coasts were sensitive for change of the criteria’s weights, particularly the eastern coast that expressed significant response

Assessment of coastal watershed erosion potential using geographic information systems and expert input for decision support

Sediment is a major impairment in many streams and rivers in the drainage basins along the northern Gulf of Mexico. The use of geospatial technologies improves assessment and decision making for the management of environmental resources and conditions for coastal watersheds. This research focuses on the development of a conceptual qualitative model enhanced with expert input for the assessment of soil erosion potential in coastal watersheds. The conceptual model is built upon five layers (slope, precipitation, soil brightness or exposure, Kactor, and stream density) like those in a standard numerical soil loss model such as the Revised Universal Soil Loss Equation (RUSLE). The conceptual model produced a continuous surface to index erosion potential. Pearson’s correlation coefficient was used to identify variable sensitivity. The model was most sensitive to Kactor variable, followed by soil brightness, stream density, and slope. The model was not sensitive to the precipitation variable due to the lack of variability across the watershed. Expert input was added to the conceptual model for erosion potential with the Analytical Hierarchy Process (AHP). The AHP is used to value the importance of criteria, providing a quantitative weight for the qualitative data. The expert input increased the overall importance of topographic features and this increased cell counts in the upper erosion potential classes. The AHP weights were altered in 1% increments ranging from plus to minus 20% producing 201 unique runs. A quartile analysis of the runs was used to define areas of model agreement. The quartile analysis allowed for the application of an analysis mask to identify areas of increased erosion potential for improved management related decisions. The conceptual and AHP erosion potential output data, including watershed management priority rankings, were published as web mapping services for story map development as a transition to a decision support system. The limits of the story map to allow user interactions with model output rendered an unacceptable platform for decision support. The story map does offer an alternative to static reports and could serve to improve dissemination of spatial data as well as technical reports and plans like a watershed management plan

Agro-ecological evaluation of sustainable area for citrus crop production in Ramsar District, Iran

Citrus growing is regarded as an important cash crop in Ramsar, Iran. Ramsar District has a temperate climate zone, while citrus is a sub-tropical fruit. Few studies on citrus crop in terms of negative environmental factors have been carried out by researchers around the world. This study aims to integrate Geographical Information System (GIS) and Analytical Network Process (ANP) model for determination of citrus suitability zones. This study evaluates the agro-ecological suitability, determine potentials and constraints of the region based on effective criteria using ANP model. ANP model was used to determine suitable, moderate and unsuitable areas based on (i) socio-economic, morphometry and hydro-climate factors using 15 layers based on experts’ opinion; (ii) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite image of the year 2003 with 98.45% overall accuracy, and (iii) developed Multiple Linear Regression (MLR) model for citrus prediction. Thereby, weighted overlay of 15 factors was obtained using GIS. In this study, the citrus orchards map of 2003 and the new map of the citrus areas of 2014 namely Citrus State Development Program (CSDP) of the study area were compared. The results of this study demonstrated: (i) suitable areas (free risk areas) based on negative environmental factors and areas which are susceptible to citrus plantation; (ii) high-risk areas which are unsuitable for citrus plantation, and (iii) the high weights derived by ANP model were assigned to altitude, frost and minimum temperature. The MLR model was successfully developed to predict citrus yield in Ramsar District by 10% error. The MLR model would propose optimum citrus crop production areas. As conclusion, the main outcome of this study could help growers and decision makers to enhance the current citrus management activities for current and future citrus planning

Using spatial multi-criteria analysis as an appraisal tool for bus rapid transit trunk and feeder routes: a case study in the City of Tshwane, South Africa

Private car use around the world has grown increasingly over the last decades. One effect of this is traffic congestion, which results in various detrimental environmental, economic and social impacts. Public transport has been identified as an effective solution to congestion. In South Africa, investment into public transport has led to the implementation of full and partial Bus Rapid Transit (BRT) systems. The policy and implementation measures of these BRT systems have been modelled, to varying degrees, according to Colombia’s TransMilenio BRT. However, BRT systems in South Africa have not been as successful as TransMilenio. Failures of South African BRTs can be traced back to many reasons, one of which is an inadequate conduction of an ex ante appraisal. This dissertation intended to close a literature gap on the use of ex ante appraisal in South African transport projects. At the time of composing this thesis (February 2017), South Africa did not have a standard appraisal tool for the selection of appropriate transport projects and road-based public transport routes. This resulted in systems that were not designed in context and, hence, underperformed for the context in which they were implemented. The contextually insensitive design of BRTs and the effects thereof constituted the conceptual departure point for this research. Accordingly, this dissertation aimed to explore Spatial MultiCriteria Analysis (SMCA) as a viable appraisal tool for BRT routes. The City of Tshwane formed the study area of the investigation. SMCA is a decision-support tool that combines multi-criteria analysis (MCA) and geographic information systems for evaluating decision problems whose criteria and alternatives have spatially explicit dimensions. This method was chosen over traditional appraisal tools such as MCA and cost-benefit analysis as it is more suited to routing problems. Suitable evaluation criteria were identified from five themes that were chosen from international and local trends: equity, transport efficiency and economic, social and environmental impact. Ultimately, composite suitability maps were generated according to the aforementioned themes, and optimal trunk and feeder routes were extracted by means of a vector-based network analysis. Four trunk and four feeder routes were quantitatively and qualitatively analysed. The quantitative analysis of the route involved determining the average impedance, route length and travel time of a route. The qualitative analysis involved determining if the optimal routes had changed to current or planned city routes. On average, trunk routes obtained a higher average impedance than feeder routes. All optimal routes differed to some degree from planned city routes. Following the determination of optimal routes, an uncertainty analysis showed that trunk routes were more sensitive than feeder routes. The sensitivity analysis also showed that the transport efficiency theme criteria were the most sensitive criteria, causing the highest mean average impedance change of all criteria. Transport efficiency criteria are thus the most important criteria in finding optimal routes. The method of research adopted in this study can be reproduced in any contemporary South African city with plans for BRT. Furthermore, the method of research can be improved upon by investigating standard evaluation criteria to be included in an SMCA routing problem to ensure a uniform appraisal standard

Using spatial multi-criteria analysis as an appraisal tool for bus rapid transit trunk and feeder routes: a case study in the City of Tshwane, South Africa

Private car use around the world has grown increasingly over the last decades. One effect of this is traffic congestion, which results in various detrimental environmental, economic and social impacts. Public transport has been identified as an effective solution to congestion. In South Africa, investment into public transport has led to the implementation of full and partial Bus Rapid Transit (BRT) systems. The policy and implementation measures of these BRT systems have been modelled, to varying degrees, according to Colombia’s TransMilenio BRT. However, BRT systems in South Africa have not been as successful as TransMilenio. Failures of South African BRTs can be traced back to many reasons, one of which is an inadequate conduction of an ex ante appraisal. This dissertation intended to close a literature gap on the use of ex ante appraisal in South African transport projects. At the time of composing this thesis (February 2017), South Africa did not have a standard appraisal tool for the selection of appropriate transport projects and road-based public transport routes. This resulted in systems that were not designed in context and, hence, underperformed for the context in which they were implemented. The contextually insensitive design of BRTs and the effects thereof constituted the conceptual departure point for this research. Accordingly, this dissertation aimed to explore Spatial MultiCriteria Analysis (SMCA) as a viable appraisal tool for BRT routes. The City of Tshwane formed the study area of the investigation. SMCA is a decision-support tool that combines multi-criteria analysis (MCA) and geographic information systems for evaluating decision problems whose criteria and alternatives have spatially explicit dimensions. This method was chosen over traditional appraisal tools such as MCA and cost-benefit analysis as it is more suited to routing problems. Suitable evaluation criteria were identified from five themes that were chosen from international and local trends: equity, transport efficiency and economic, social and environmental impact. Ultimately, composite suitability maps were generated according to the aforementioned themes, and optimal trunk and feeder routes were extracted by means of a vector-based network analysis. Four trunk and four feeder routes were quantitatively and qualitatively analysed. The quantitative analysis of the route involved determining the average impedance, route length and travel time of a route. The qualitative analysis involved determining if the optimal routes had changed to current or planned city routes. On average, trunk routes obtained a higher average impedance than feeder routes. All optimal routes differed to some degree from planned city routes. Following the determination of optimal routes, an uncertainty analysis showed that trunk routes were more sensitive than feeder routes. The sensitivity analysis also showed that the transport efficiency theme criteria were the most sensitive criteria, causing the highest mean average impedance change of all criteria. Transport efficiency criteria are thus the most important criteria in finding optimal routes. The method of research adopted in this study can be reproduced in any contemporary South African city with plans for BRT. Furthermore, the method of research can be improved upon by investigating standard evaluation criteria to be included in an SMCA routing problem to ensure a uniform appraisal standard

Multi-criteria suitability analysis and spatial interaction modeling of retail store locations in Ontario, Canada

GIS-based decision analysis is increasingly used by retailers to address the complexity and cost of investment in retail store location decisions. This study conceptualizes and represents nine criteria in a GIS-based multi-criteria decision analysis of 4.7 million potential retail store locations. From topographic statistics to spatial interaction modelling, the study utilizes criteria of varied complexity to analyze the statistical and spatial distribution of highly suitable locations for a retail store. The study further examines how the spatial representations of criteria based on the Huff model affects the distribution of suitable locations. The results show that although Toronto dominates the retail landscape in Ontario, key regions are found in Guelph, Kitchener-Waterloo and Cambridge. Results show that the incorporation of network-based spatial interaction costs in Huff’s model produces more spatially heterogeneous sales estimates than Euclidean-based spatial interactions. Future research efforts in improving various components of the suitability analysis, as well as the scaling and regional parameterization of spatial interaction models are also discussed

Web 2.0-based Collaborative Multicriteria Spatial Decision Support System: A Case Study of Human-Computer Interaction Patterns

The integration of GIS and Multicriteria Decision Analysis (MCDA) capabilities into the Web 2.0 platform offers an effective Multicriteria Spatial Decision Support System (MC-SDSS) with which to involve the public, or a particular group of individuals, in collaborative spatial decision making. Understanding how decision makers acquire and integrate decision-related information within the Web 2.0-based collaborative MC-SDSS has been one of the major concerns of MC-SDSS designers for a long time. This study focuses on examining human-computer interaction patterns (information acquisition behavior) within the Web 2.0-based MC-SDSS environment. It reports the results of an experimental study that investigated the effects of task complexity, information aids, and decision modes on information acquisition metrics and their relations. The research involved three major steps: (1) developing a Web 2.0-based analytic-deliberative MC-SDSS for parking site selection in Tehran, Iran to analyze human-computer interaction patterns, (2) conducting experiments using this system and collecting the human-computer interaction data, and (3) analyzing the log data to detect the human-computer interaction patterns (information acquisition metrics). Using task complexity, decision aid, and decision mode as the independent factors, and the information acquisition metrics as the dependent variables, the study adopted a repeated-measures experimental design (or within-subjects design) to test the relevant hypotheses. Task complexity was manipulated in terms of the number of alternatives and attributes at four levels. At each level of task complexity, the participants carried out the decision making process in two different GIS-MCDA modes: individual and group modes. The decision information was conveyed to participants through common map and decision table information structures. The map and table were used, respectively, for the exploration of the geographic (or decision) and criterion outcome spaces. The study employed a process-tracing method to directly monitor and record the decision makers’ activities during the experiments. The data on the decision makers’ activities were recorded as Web-based event logs using a database logging technique. Concerningiv task complexity effects, the results of the study suggest that an increase in task complexity results in a decrease in the proportion of information searched and proportion of attribute ranges searched, as well as an increase in the variability of information searched per attribute. This finding implies that as task complexity increases decision makers use a more non-compensatory strategy. Regarding the decision mode effects, it was found that the two decision modes are significantly different in terms of: (1) the proportion of information search, (2) the proportion of attribute ranges examined, (3) the variability of information search per attribute, (4) the total time spent acquiring the information in the decision table, and (5) the average time spent acquiring each piece of information. Regarding the effect of the information aids (map and decision table) on the information acquisition behavior, the findings suggest that, in both of the decision modes, there is a significant difference between information acquisition using the map and decision table. The results show that decision participants have a higher number of moves and spend more time on the decision table than map. The study presented in this dissertation has implications for formulating behavioral theories in the spatial decision context and practical implications for the development of MC-SDSS. Specifically, the findings provide a new perspective on the use of decision support aids, and important clues for designers to develop an appropriate user-centered Web-based collaborative MC-SDSS. The study’s implications can advance public participatory planning and allow for more informed and democratic land-use allocation decisions