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All Journal International Journal of Public Health Science (IJPHS) Indonesian Journal of Geography Geo Media: Majalah Ilmiah dan Informasi Kegeografian Media Komunikasi Geografi Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Jurnal Teknosains Geoplanning : Journal of Geomatics and Planning Majalah Geografi Indonesia JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Ketahanan Nasional JURNAL AGROTEKNOLOGI Forum Geografi GEA, Jurnal Pendidikan Geografi Jurnal Fisika FLUX Journal of Applied Geospatial Information Jurnal Geografi Forest and Society International Journal of Remote Sensing and Earth Sciences (IJReSES) JAGAT (Jurnal Geografi Aplikasi dan Teknologi) Jurnal Geosains dan Remote Sensing (JGRS) geoedusains: Jurnal Pendidikan Geografi GEOGRAPHIA: Jurnal Pendidikan dan Penelitian Geografi JKKI : Jurnal Kedokteran dan Kesehatan Indonesia Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Manusia dan Lingkungan Aerospace Engineering IJES : Indonesian Journal of Environmental Sustainability. The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Prima Widayani
Magister Penginderaan Jauh, Fakultas Geografi, Universitas Gadjah Mada
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Journal : Forum Geografi

 1 
Evidence Based Landslide Hazard Mapping in Purworejo using Information Value Model Approach Sudaryatno, Sudaryatno; Widayani, Prima; Wibowo, Totok Wahyu; Wiratmoko, Bagus; Nurbandi, Wahyu
Forum Geografi Vol 33, No 1 (2019): July 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i1.7592

Abstract

Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.
Evidence Based Landslide Hazard Mapping in Purworejo using Information Value Model Approach Sudaryatno Sudaryatno; Prima Widayani; Totok Wahyu Wibowo; Bagus Wiratmoko; Wahyu Nurbandi
Forum Geografi Vol 33, No 1 (2019): July 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i1.7592

Abstract

Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.
Implementing Support Vector Machine Algorithm for Early Slum Identification in Yogyakarta City, Indonesia Using Pleiades Images Prima Widayani; Achmad Fadilah; Irfan Zaki Irawan; Kapil Ghosh
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.
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.
Co-Authors Achmad Fadhilah Achmad Fadilah Ade Febri Sandhini P Agatha Andriantari Agus Joko Pitoyo Akmal Hafiudzan Akmal Hafiudzan Andung Bayu Sekaranom Arief Wicaksono Arrafi, Muhammad Bagus Wiratmoko Bowo Susilo Dewi Miska Indrawati Dyah Kusuma, Dyah Edi Suharyadi Erika Yuliantari Fadilah, Achmad Fathilda, Intan Khaeruli Febrianti, Ni Kadek Oki Ghosh, Kapil Hamim Zaky Hadibasyir Hari Kusnanto Hidayatullah, Faqih Huwaida Nur Salsabila Indrawati, Dewi Miska Ira Nurmala Hani Irawan, Irfan Zaki Irfan Zaki Irawan Irfan Zaki Irawan Irsan, Laode Muhamad Iswari Nur Hidayati Kapil Ghosh Kusbaryanto Mahendra, Auzaie Ihza Mizan, Rahmat azul Muhammad Arrafi Muhammad Kamal Muhammad Kamal Muhammad Minan Chusni Muhammad Sufwandika Wijaya Muhammad Sufwandika Wijaya Muhammad Sufwandika Wijaya Murti Budi Santosa, Sigit Heru Ni Kadek Oki Febrianti Nur Mohammad Farda Nur Mohammad Farda Nurbandi, Wahyu Nurhadi, Muhammad Nurul Astuti, Nurul Nurweni, Susi Nurwita Mustika Sari Nurwita Mustika Sari Projo Danoedoro Projo Danoedoro Projo Danoedoro R. Suharyadi Ramadhan Pasca Wijaya Rina Febriany Sandy Budi Wibowo Sanjiwana Arjasakusuma Sanjiwana Arjasakusuma, Sanjiwana Santosa, Sigit Herumurti Budi Seandrasto Abi Kharis Wardhani Shandra S Pertiwi Sigit Heru Murti Sitti Rahmah Umniyati Sudaryatno Sudaryatno Sugeng Juwono Mardihusodo Suherningtyas, Ika Afianita Totok Gunawan Totok Wahyu Wibowo Tri Wulandari Kesetyaningsih Ulfa Aulia Syamsuri Vandam Caesariadi Bramdito Wahyu Nurbandi Wiratmoko, Bagus Wirayuda, I Kade Alfian Kusuma Zahrotunisa, Siti