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Fahmi Arif Kurnianto
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Geosfera Indonesia
Published by Universitas Jember
ISSN : 25989723     EISSN : 26148528     DOI : -
Core Subject : Science, Social,
Earth & Planetary Sciences Environmental Science Social Sciences
Geosfera Indonesia : | ISSN: 2598-9723 (Print)| ISSN: 2614-8528 (Online) is published by Department of Geography Education, University of Jember, Indonesia. We accept mainly research-based articles related to geography. Geosfera Indonesia welcomes contributions in such areas of current analysis in: (1) Geography Education, (2) Geography (Physical Geography and Human Geography), (3) Geographic Information System (GIS), (4) Remote Sensing, (5) Environmental Science, and (6) Disaster Mitigation. Since volume 1, it is published three times a year in April, August, and December. Every issue consisted of 12 articles.
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Articles 8 Documents
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Search results for , issue "Vol 6 No 1 (2021): GEOSFERA INDONESIA" : 8 Documents clear
Back-matter (Reviewer Acknowledgement, Back Cover) Fahmi Arif Kurnianto
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.24149

Abstract

Quantifying The Significance of Distance to Temporal Dynamics of Covid-19 Cases in Nigeria Using a Geographic Information System Ifeyinwa Sarah Obuekwe; Umar Saleh Anka; Sodiq Opeyemi Ibrahim; Usman Ahmad Adam
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.21405

Abstract

The coronavirus disease 2019 (COVID-19) is caused by a new strain of coronavirus that spreads primarily by close contact. Although Nigeria adopted lockdown measures, no defined strategies were used in setting the distance threshold for these lockdowns. Hence, understanding the drivers of COVID-19 is pivotal to an informed decision for containment measures in the absence of vaccines. Spatial and temporal analyses are crucial drivers to apprehending the pattern of diseases over space and time. Thus, this study aimed to quantify the significance of distance to the temporal dynamics of COVID-19 cases in Nigeria using the Geographic Information System. Incremental spatial autocorrelation was used to analyze datasets of each month in ArcGIS. March, April, May, and June exhibited patterns with no significant peaks, while July and August exhibited patterns with two statistically significant peaks. The first and second peaks of July were 301,338.39 and 365,947.83 meters, respectively, while August was 301,338.39 and 336,128.09 meters, respectively. Therefore, a significant difference in the clustering of COVID-19 over distances between July and August was established. This indicated that progression in the spread of the virus increased the virus's spatial coverage while the distance of risk of exposure decreased. This study's findings could be utilized to establish maximum movement restriction areas to contain the spread of COVID-19. Keywords: Distance; Incremental spatial autocorrelation; Covid-19; Disease; Nigeria Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Assessment of Water Balance at Mayang Watershed, East Java Ariska Mia Christiwarda Sihombing; Indarto Indarto; Sri Wahyuningsih
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.23111

Abstract

Mayang Watersheds frequently hit by floods during the rainy season and drought during the dry season. This study aims to assess the water balance by calculating water resource availability and water demand in the Mayang watershed. The Water Evaluation and Planning (WEAP) model was used as the primary tool for the analysis. The supply of water comes only from precipitation. Demand was calculated based on the water demand for irrigation, domestic, urban, industrial, and livestock uses. The unit of time to calculate the water balance is ten days. It means that each month is divided into three-time steps. Analysis of the WEAP is based on the water demand from 2002 to 2019. The results showed that from 3rd December to 1st May, the Mayang river and its tributaries could supply all demand sites up to 100%. However, unmet demand occurs from 2nd May to 2nd December. The highest first unmet demand occurred in October, with 0.67 million m3. The management of water resources, especially in terms of distribution during the rainy season and dry season, must be considered. Keywords: Water balance; Water supply; Water demand; Mayang; Watershed; WEAP Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Development of Web-Based GIS Alert System for Informing Environmental Risk of Dengue Infections in Major Cities of Pakistan Naureen Zainab; Aqil Tariq; Saima Siddiqui
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.20792

Abstract

Dengue is one of the emerging major public health problems, and its incidence varies with climate conditions. It affects millions of people's lives owing to unusual socioeconomic conditions and epidemiological factors. This study was designed to build a web-based GIS alert system for dengue data management and analysis which would centralize information and make it accessible to all relevant stakeholders before, during, and after crises. Three geographical regions were selected in this study. The user interface of the dengue alert system was developed based upon MapGuide. Results indicate that risk level was mainly associated with Breteau Index. Karachi and Lahore were at their highest risk, i.e., level 4. Islamabad and Chakwal were also at the highest risk, i.e., level 4. Attock had high risk, i.e., level 3 followed by Haripur with minimal level 1. The high Breteau Index showed a direct relationship to high potential transmission of dengue outbreaks, a more significant peak of dengue was the result of monsoons, while smaller peaks were observed due to domestic water storage. Hence, it was concluded that monsoon is the best suitable season for the development of dengue. Web-Based GIS Alert System for dengue data management and analysis was developed, centralizing information and making it accessible to all relevant stakeholders before, during & after a crisis. This program creation will provide a more analytical forum for advising multiple levels of risk and an experimental method for measuring the effect of different factors on risk level distribution by adjusting the component's weighting. Keywords : Dengue; GIS analysis; GUI; Alert system; Breteau index; Weighted overlay Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index Ginjo Gitima; Abiyot Legesse; Dereje Biru
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.20718

Abstract

Climate variability adversely affects rural households in Ethiopia as they depend on rain-fed agriculture, which is highly vulnerable to climate fluctuations and severe events such as drought and pests. In view of this, we have assessed the impacts of climate variability on rural household’s livelihoods in agricultural land in Tarchazuria district of Dawuro Zone. A total of 270 samples of household heads were selected using a multistage sampling technique with sample size allocation procedures of the simple random sampling method. Simple linear regression, the standard precipitation index, the coefficient of variance, and descriptive statistics were used to analyze climatic data such as rainfall and temperature. Two livelihood vulnerability analysis approaches, such as composite index and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) approaches, were used to analyze indices for socioeconomic and biophysical indicators. The study revealed that the variability patterns of rainfall and increasing temperatures had been detrimental effects on rural households' livelihoods. The result showed households of overall standardized, average scores of Wara Gesa (0.60) had high livelihood vulnerability with dominant major components of natural, physical, social capital, and livelihood strategies to climate-induced natural hazards than Mela Gelda (0.56). The LVI-IPCC analysis results also revealed that the rural households in Mela Gelda were more exposed to climate variability than Wara Gesa and slightly sensitive to climate variability, considering the health and knowledge and skills, natural capitals, and financial capitals of the households. Therefore, interventions including road infrastructure construction, integrated with watershed management, early warning information system, providing training, livelihood diversification, and SWC measures' practices should be a better response to climate variability-induced natural hazards. Keywords: Households; Livelihood Vulnerability Index; climate variability; Tarchazuria District Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Rethinking Urbanization: A Transit-Information-Communication –Technology-Oriented Development Path for the Developing Countries and Post-Industrial Towns Schuman Lam; Heng Li; Ann T.W. Yu
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.20810

Abstract

This study explores a new path of urbanization to enhance the conventional economy-led urban development practice by conducting an urban quality of life (Uqol) survey. It analyzes the Uqol evaluation gap caused by demographic attributes between developing countries, developed countries, and post-industrial town. We adopted a mixed-methods research design, including a literature review and an Uqol survey, to suggest the transit-oriented-development (TOD) and information-communication-technology (ICT) based urban-rural development concept. The finding indicates a disparity of Uqol mean score rankings among the developing countries, developed countries, and the marginalized post-industrial town. It highlights the health, transportation, socio-economic, and technological development in the developing countries strongly desired. Furthermore, Kruskal-Wallis H-test and Mann-Whitney U-test results show significant differences in economy, technology-ICT, smart living, and lifestyle within education, profession, age, and country groups. It clarifies that the well-being gap is shaped by demography and exhibited geographically, which implies TOD-ICT advancement can break down geographical barriers for achieving sustainable growth in remote areas. Supported by the planetary urbanization theory, the human-technology-driven urban development process would facilitate the maturity and implementation of the proposed TOD-ICT-based urban-ruralism (UxR) concept for enhancing the future global urbanization process. Keywords : Human and Social Geography; Information-Communication-Technology; Urban Policymaking; Transit-Oriented-Development; Urban Quality of Life Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Front-matter (Front Cover, Editorial Team, and Table of Contents) Fahmi Arif Kurnianto
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.24148

Abstract

Landslide Hazard Analysis Using a Multilayered Approach Based on Various Input Data Configurations Ilyas Ahmad Huqqani; Tay Lea Tien; Junita Mohamad-Saleh
Geosfera Indonesia Vol 6 No 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.23347

Abstract

Landslide is a natural disaster that occurs mostly in hill areas. Landslide hazard mapping is used to classify the prone areas to mitigate the risk of landslide hazards. This paper aims to compare spatial landslide prediction performance using an artificial neural network (ANN) model based on different data input configurations, different numbers of hidden neurons, and two types of normalization techniques on the data set of Penang Island, Malaysia. The data set involves twelve landslide influencing factors in which five factors are in continuous values, while the remaining seven are in categorical/discrete values. These factors are considered in three different configurations, i.e., original (OR), frequency ratio (FR), and mixed-type (MT) data, which act as an input to train the ANN model separately. A significant effect on the final output is the number of hidden neurons in the hidden layer. In addition, three data configurations are processed using two different normalization methods, i.e., mean-standard deviation (Mean-SD) and Min-Max. The landslide causative data often consist of correlated information caused by overlapping of input instances. Therefore, the principal component analysis (PCA) technique is used to eliminate the correlated information. The area under the receiver of characteristics (ROC) curve, i.e., AUC is also applied to verify the produced landslide hazard maps. The best result of AUC for both Mean-SD and Min-Max with PCA schemes are 96.72% and 96.38%, respectively. The results show that Mean-SD with PCA of MT data configuration yields the best validation accuracy, AUC, and lowest AIC at 100 number of hidden neurons. MT data configuration with the Mean-SD normalization and PCA scheme is more robust and stable in the MLP model's training for landslide prediction. Keywords: Landslide; ANN; Hidden Neurons; Normalization; PCA; ROC; Hazard map Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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