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All Journal Geo Media: Majalah Ilmiah dan Informasi Kegeografian Media Komunikasi Geografi Jurnal Ketahanan Nasional Forum Geografi Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktik dalam Bidang Pendidikan dan Ilmu Geografi Jurnal Geografi Jurnal Pengabdian Pada Masyarakat Abdimas Mandalika Journal of Demography, Etnography, and Social Transformation
Suherningtyas, Ika Afianita
Universitas Amikom Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Engineering Environmental Science Social Sciences Other

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Journal : forum geografi

 1 
Analysis of Local Spatial Data Infrastructure to Support Volcanic Mudflow Mitigation along Putih River, Magelang Regency, Central Java Province, Indonesia Permatasari, Afrinia Lisditya; Suherningtyas, Ika Afianita; Wiguna, Putu Perdana Kusuma
Forum Geografi Vol 34, No 1 (2020): July 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v34i1.11169

Abstract

One of the most devastating disasters in Indonesia was the Mount Merapi eruption in 2010. After the eruption there still exists the secondary hazard of volcanic mudflow, which has caused damage and casualties. Volcanic mudflow is a mixture of pyroclastic material and rainwater, meaning that in the rainy season the area along rivers becomes a high volcanic mudflow hazard, including the area along Putih River in Magelang Regency, Central Java Province. The development of Spatial Data Infrastructure (SDI) plays an important role in disaster management, especially in disaster mitigation efforts. Building an SDI which shares information on spatial conditions in the area along the Putih River could save many lives and reduce the risk from volcanic mudflow. This research was conducted employing interview surveys, field surveys and secondary data collection at government institutions. The results of the analysis have provided a geoportal prototype as an information gateway for the mitigation of volcanic mudflow along the Putih River and the reduction of disaster risk both for the government and community.
Analysis of Local Spatial Data Infrastructure to Support Volcanic Mudflow Mitigation along Putih River, Magelang Regency, Central Java Province, Indonesia Afrinia Lisditya Permatasari; Ika Afianita Suherningtyas; Putu Perdana Kusuma Wiguna
Forum Geografi Vol 34, No 1 (2020): July 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v34i1.11169

Abstract

One of the most devastating disasters in Indonesia was the Mount Merapi eruption in 2010. After the eruption there still exists the secondary hazard of volcanic mudflow, which has caused damage and casualties. Volcanic mudflow is a mixture of pyroclastic material and rainwater, meaning that in the rainy season the area along rivers becomes a high volcanic mudflow hazard, including the area along Putih River in Magelang Regency, Central Java Province. The development of Spatial Data Infrastructure (SDI) plays an important role in disaster management, especially in disaster mitigation efforts. Building an SDI which shares information on spatial conditions in the area along the Putih River could save many lives and reduce the risk from volcanic mudflow. This research was conducted employing interview surveys, field surveys and secondary data collection at government institutions. The results of the analysis have provided a geoportal prototype as an information gateway for the mitigation of volcanic mudflow along the Putih River and the reduction of disaster risk both for the government and community.
Spatial Analysis of Mangrove Distribution Using Landsat 8 Oli in Badung Regency and Denpasar City, Bali Province, Indonesia Putu Perdana Kusuma Wiguna; Ni Wayan Sri Sutari; Erik Febriarta; Afrinia Lisditya Permatasari; Ika Afianita Suherningtyas; Nur Ainun Harlin Jennie Pulungan; Tri Tanami Sukraini; Mutiara Gani
Forum Geografi Vol 36, No 1 (2022): July 2022
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v36i1.14711

Abstract

Bali is an island situated among the Indonesian archipelago with huge potential to host mangrove forests. Using remote sensing technology advances, satellite images, such as Landsat images, might be employed to analyse mangrove forest distribution and density. This paper presents an analysis of mangrove distribution in Badung Regency and Denpasar City, Bali, as a basis for the management and conservation of mangrove ecosystems. This study used Landsat 8 OLI images and a vegetation index to analyse the mangrove forest distribution and density in this area. It started by identifying mangrove forests using the RGB 564 band and continued to distinguish between mangrove and non-mangrove objects using unsupervised classification, before analysing mangrove density using the NDVI formula. The results show that the mangrove forest area in 2020 was 1,269.20 ha, with an accuracy rate of 83%. Mangroves were found on the deepest or most curved coastline of the Benoa Bay area, on enclosed waters. This distribution follows the river network in the lower reach, which has thick deposits and is uninfluenced by large currents and waves. Based on the vegetation index analysis results, the mangrove forest area observed mainly had a moderate density, with a total area of 510.85 ha (40%), followed by high density (413.15 ha/ 33%) and low density (340.51 ha/ 27%).
Analysis of Vulnerability to Transmission of the Covid-19 based on Building Function at Padukuhan Mancasan Kleben, Pandowoharjo, Sleman, Yogyakarta Afrinia Lisditya Permatasari; Ika Afianita Suherningtyas; Erik Febriarta; Putu Perdana Kusuma Wiguna
Forum Geografi Vol 35, No 2 (2021): December 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v35i2.13755

Abstract

Coronavirus Disease (COVID-19) pandemic is currently being a concern in all parts of the world, including Indonesia. Yogyakarta Special Region, especially Sleman Regency, is a red zone, which is an area that has a very high transmission rate of Covid-19. Padukuhan Mancasan Kleben, is one of the hamlets located near the government center of Sleman Regency where community activity and mobility are quite high. There are many business buildings located along the main road. The purpose of this research is to analyze the vulnerability to transmission of Coronavirus Disease (COVID-19) based on building function using Analytical Hierarchy Process (AHP) and Spatial Multi Criteria Evaluation (SMCE) methods. Types of buildings as houses and store are identified using Unmanned Aerial Vehicle (UAV) image. Types of buildings used as physical variables in the analysis. Based on the result, from total of 363 buildings, there are 35 buildings that have a high level of vulnerability and 328 buildings with low vulnerability. A low level of vulnerability is found in buildings that function as shophouse. Meanwhile, the low level of vulnerability is found in buildings used as houses and public facilities. This is because during the pandemic, several public facilities in Mancasan Kleben are not yet operational. Mitigation efforts that need to be implemented are increasing awareness of ourselves and the surrounding environment. The implementation of healthy living habits by implementing CITA MAS JAJAR, avoiding crowds and not traveling if it is not too important, can help prevent the transmission of Coronavirus Disease (COVID-19)
Co-Authors . Rizky Afrinia Lisditya Permatasari Afrinia Lisditya Permatasari Agus Joko Pitoyo Agus Joko Pitoyo Ajeng Larasati Erik Febiarta Erik Febriarta Erik Febriarta Erik Febriarta Erik Febriarta Eva Kurnia Setyawati Laela Nurul Istiqomah Laela Nurul Istiqomah Mutiara Gani NI PUTU SRI SUTARI Nucifera, Fitria Nur Ainun Harlin Jennie Pulungan Permatasari, Afrinia Lisditya Prima Widayani Putu Perdana Kusuma Wiguna Putu Perdana Kusuma Wiguna Rhisa Aidilla Suprapto Riasasi, Widiyana Sejati, Sadewa Purba Sekarsih, Fitria Nuraini Sola Tri Astuti Tri Tanami Sukraini Vidyana Arsanti, Vidyana Zulham Huzaeni