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Forum Geografi
Published by Universitas Muhammadiyah Surakarta
ISSN : 08520682     EISSN : 24603945     DOI : -
Core Subject : Science,
Earth & Planetary Sciences
Forum Geografi, Indonesian Journal of Spatial and Regional Analysis (For. Geo) is an open access, peer-reviewed journal that will consider any original scientific article for expanding the field of geography. The journal publishes articles in both physical and human geography specialties of interest to spatial analysis and regional analysis in (but not limited) Indonesia by applying GIS and/or remote sensing techniques.
Arjuna Subject : -
Articles 1,205 Documents
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Friends and Neighbours: Electoral Geography of 2020 Local Election in Metro City, Lampung, Indonesia Warganegara, Arizka; Darmastuti, Ari; Hertanto, Hertanto; Krisbintoro, R Sigit; Febriansyah, Muhammad; Pramono, Wahyu Tyas
Forum Geografi Vol 37, No 2 (2023): December 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i2.23316

Abstract

This article discusses local political dynamics in Indonesia, notably in the city of Metro. There are several factors why a particular candidate is more politically electable than others, including ethno-religious factors and money. Moreover, a traditional factor that needs to be considered in the study of electoral geography is the influence of the spatial effect upon voting behaviour. In the election, demographics and geography are two important factors in voting behaviour. The local election resulted in a competitive and dynamic political contest among the local elite in Metro. The result of the 2020 local election was particularly interesting because the independent candidate won and defeated the party-based candidate. This is a mixed methods approach combining the data from interviews and a qualitative survey. This research aims to analyse the spatial factor in Metro’s local election, looking at why a certain candidate won in a particular area and how the geographical factor influenced voting behaviour. Secondly, the result of the qualitative survey supported the finding that voters still consider ethno-religious factor. The finding obtained by this research reveals two significant narratives, specifically the crucial factor of ethno-religious sentiment on voting preference and the spatial factor related to residency in securing a victory for the candidate in the local election. Essentially, research concludes that the spatial factor is of importance in the context of Metro’s local election and supports Woolstencroft's (1980) classical concept of electoral geography comprising “friends and neighbours”.
Implementing Support Vector Machine Algorithm for Early Slum Identification in Yogyakarta City, Indonesia Using Pleiades Images Widayani, Prima; Fadilah, Achmad; Irawan, Irfan Zaki; Ghosh, Kapil
Forum Geografi Vol 37, No 1 (2023): July 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i1.15248

Abstract

Slums are one of the urban problems that continue to get the attention of the government and the city of Yogyakarta. Over time, cities continue to experience changes in land use due to population growth and migration. Therefore, it is necessary to monitor the existence of slums continuously. The objectives of this study are to conduct early identification of the slum using the Support Vector Machine (SVM) Algorithm, which is applied to the Pleiades Image in parts of Yogyakarta City, to test the accuracy of the slum mapping results generated from the SVM compared to the Slum Map of the KOTAKU Program. The data used are Pleiades Image, administrative maps, and existing slum maps of the KOTAKU Program, which are used to test the accuracy. The method used is Machine Learning with a Support Vector Machine Algorithm. The parameters used for early identification of the slums are the characteristics of the object (characteristics of buildings), settlement (density and shape), and the environment (location and its proximity to rivers and industries). We separate slum and non-slum based on texture, morphology, and spectral approaches. Based on the accuracy test results between the SVM classification results map of the slum and the map from the KOTAKU Program, the accuracy is 86.25% with a kappa coefficient of 0.796.
Machine Learning-Based Rice Field Mapping in Kulon Progo using a Fusion of Multispectral and SAR Imageries Khoirurrizqi, Yusri; Sasongko, Rohmad; Utami, Nur Laila Eka; Irbah, Amanda; Arjasakusuma, Sanjiwana
Forum Geografi Vol 37, No 2 (2023): December 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i2.20304

Abstract

The land-conversion of rice fields can reduce rice production and negatively impact food security. Consequently, monitoring is essential to prevent the loss of productive agricultural land. This study uses a combination of Sentinel-2 MSI, Sentinel-1 SAR, along with SRTM (elevation and slope data) to monitor rice fields land-conversion. NDVI, NDBI and NDWI indices are transformed from the annual median composite Sentinel-2 MSI images used to identify different rice fields with another object. A monthly median composite of SAR images from Sentinel-1 data are used to identify cropping patterns of rice fields in the inundation phase. The classification is performed by using the Random Forest machine learning algorithm in the Google Earth Engine (GEE) platform. Random Forest classification is run using 1000 trees, with a 70:30 ratio of training and testing data from sample features extracted by visual interpretation of high resolution Google Earth imagery. In this study, Random Forest classification is effective in computing a high amount of multi-temporal and multi-sensory data to map rice-field land conversion with an accuracy rate of 96.16% (2021) and 95.95% (2017) for mapping paddy fields. From the multitemporal rice field maps in 2017—2021, a conversion of 826.66 hectares of rice-fields to non-rice fields was identified. Based on the spatial distribution, the conversion from rice-field to non-rice field is higher at the area near the roads, built area and Yogyakarta International Airport. Therefore, it is important to assess and ensure that National Strategic Projects are managed with due regard to environmental impacts and food security. 
Multi-Hazard Analysis in Gunungkidul Regency Using Spatial Multi-Criteria Evaluation Mustikaningrum, Melati; Widhatama, Adrianus Farrel; Widantara, Khrisna Wasista; Ibrohim, Mirza; Hibatullah, Muhammad Fikri; Larasati, Rinanda Amdalista Prastia; Utami, Sri; Hadmoko, Danang Sri
Forum Geografi Vol 37, No 1 (2023): July 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i1.19041

Abstract

This study has two aims: to determine the spatial distribution of multi-hazard levels and to discover the interactions, interdependencies, and effects that cascade among hazards in Gunungkidul Regency, Special Region of Yogyakarta. A multi-hazard map was created with a scale of 1:250,000 and modelled using SMCE (Spatial Multi-Criteria Evaluation). The conditioning factors used included slope, rainfall, historical data, river distance, geomorphology, land cover, lithology, and fault distance. The selected conditioning factors for each hazard were then weighted using weighted overlay analysis. The results showed that the area of Gunungkidul can be included in the high-risk category for floods, since the probability of flooding is 56.72%, the probability of landslides is 9.14%, that of drought is 48.86%, and that of seismic disturbance is 20.83%. (Multi-hazard maps are created by overlaying flood, landslide, seismic, and drought hazard maps.) After these risk factors were calculated, the regions on the multi-hazard map were re-categorized into five hazard classes. All areas in Gunungkidul Regency have multiple hazards, with risk factors of different magnitudes. The interaction between hazards can generate new hazards that are called cascading hazards. The cascading hazards in the study area are most likely to occur in the north of Gunungkidul Regency with its very high seismic and landslide hazard risk factors, due to the geological and geomorphological conditions of the Baturagung Structural Hills.
Reflections on the Impact of Urban Sprawl on the Architecture of the City: Lessons from Benin City, Nigeria Odeyale, Timothy Oluseyi
Forum Geografi Vol 37, No 1 (2023): July 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i1.22289

Abstract

This paper focuses on Benin City, Nigeria, as a case study to explore urban sprawl and its associated problems resulting from unplanned and uncontrolled spatial expansion. Informal settlements house approximately 45% of Nigeria's urban population, leading to a range of land and environmental challenges. The study investigates how sustainable development goals can be realized through efficient sustainable planning and urban design concepts, with a focus on managing urban sprawl in the city. The methodology comprises a literature review, field investigation of unplanned or squatter settlements in a selected part of Benin City through the administration of 201 questionnaires, and an analysis of its developments and physical transformations. Understanding the issues of urban sprawl arising from the rapid spatial expansion of Benin City is crucial for achieving a well-organized, planned, orderly, and sustainable environment. This paper provides valuable insights and information to facilitate effective urban planning in the study area. Additionally, it offers guidance to practitioners and developers on the adoption of sustainability measures in their projects. The findings of this study contribute to expanding the knowledge horizon and serve as a reference for further research on spatial expansion and the incidence of sprawl in urban centers throughout Nigeria.

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