Articles
<![CDATA[Identifikasi Luasan Banjir Rob di Kota Semarang Pada Tanggal 24 Mei 2022 Menggunakan Citra Landsat ]]>
<![CDATA[Andi Nur Rahman]]>;
<![CDATA[Nia Kurniadin]]>;
<![CDATA[Romansah Wumu]]>;
<![CDATA[Shabri Indra Suryalfihra]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Sciences Vol. 1 No. 2 (2023): March 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
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DOI: 10.51967/gets.v1i2.16
<![CDATA[ Tidal floods are floods that occur as a result of sea tides that inundate areas that have a lower elevation than sea level. The occurrence of tidal floods is due to sea level rise caused by tides, external forces such as water, wind, or swell (waves caused from a long distance), and storms which are natural phenomena that often occur at sea. A tidal flood in Semarang City on May 23, 2022, occurred with a height of 1.5 meters, occurred in the Tanjung Emas Port area. This tidal flood became the most severe flood in 2022. The utilization of remote sensing technology by using Landsat satellite imagery can be maximized to obtain information about tidal flood events that occurred in the city of Semarang. The purpose of this study was to find out how to identify the area of flooding using Landsat 8 and Landsat 9 imagery using the NDWI method and to determine the extent of the tidal flood that occurred on May 24, 2022, by comparing the wettability values of satellite imagery before and after the tidal flood. The results obtained are in the form of changes in the area of water bodies due to tidal flooding on the north coast of Semarang City in the Tugu sub-district 39.982 Ha; West Semarang 16.765 Ha; North Semarang 5.174 Ha; East Semarang 0.104 Ha; and Genuk 33.393 Ha.]]>
<![CDATA[Analisis Spasial Temporal Klorofil-a Perairan Ponelo Kepulauan Provinsi Gorontalo Tahun 2018-2022 Menggunakan Data Landsat 8 ]]>
<![CDATA[Romansah Wumu]]>;
<![CDATA[Nia Kurniadin]]>;
<![CDATA[Shabri Indra Suryalfihra]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Sciences Vol. 1 No. 2 (2023): March 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
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DOI: 10.51967/gets.v1i2.17
<![CDATA[Indonesia's maritime area covers approximately 3.25 million km2, which means that 70% of Indonesia's total area is comprised of the ocean. This indicates the enormous potential that Indonesia's ocean holds. The ocean is a crucial resource for the Ponelo Islands community, whose main livelihood is fishing. The marine ecosystem is vulnerable to environmental changes and pollution. Chlorophyll-a can serve as an indicator of the health of marine waters. Mapping the distribution of chlorophyll-a on the ocean's surface can be achieved through remote sensing technology. The study utilized the Nuriya Algorithm (2010) to derive the chlorophyll-a content in surface waters using Landsat-8 data from 2018-2021. Data processing is done through Google Earth Engine (GEE) which has the ability to process large amounts of data quickly (Big Data). The findings indicate an increase in chlorophyll-a content in the waters of Ponelo Islands at the beginning (DOY 0-20) and end (DOY 300-325) of the year. On a spatial scale, the average chlorophyll-a is widely distributed in the waters of Ponelo but is more concentrated in the coastal areas. This indicates that coastal areas of the Ponelo Islands may be more vulnerable to pollution and environmental changes and require special attention in environmental management and marine ecosystem conservation efforts.]]>
<![CDATA[Analisis Deformasi Jalan Penghubung Antara Kelurahan Sanga-Sanga Dalam dan Kelurahan Pendingin Tahun 2015 dan 2021 Menggunakan Metode Interferometry Synthetic Aperture Radar ]]>
<![CDATA[Taufan Yanuar Muslim]]>;
<![CDATA[Nia Kurniadin]]>;
<![CDATA[Dyah Widyasasi]]>;
<![CDATA[Romansah Wumu]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 2 No. 1 (2023): September 2023 ]]>
Publisher : <![CDATA[Politeknik Pertanian Negeri Samarinda ]]>
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DOI: 10.51967/gets.v2i1.28
<![CDATA[The rise of coal mining in the East Kalimantan area which is close to public road access is thought to affect the quality and sustainability of surrounding public road access. The aim of this research is to determine the use of remote sensing data to analyze land subsidence or deformation that occurs on the connecting road between Sanga-Sanga Dalam Village and Pendingin Village, Sanga-Sanga District, Kutai Kartanegara Regency. The method used in this research is quantitative descriptive, namely determining ground deformation on roads obtained by analyzing Sentinel-1 imagery in 2015 and Sentinel-1 imagery in 2021. Ground deformation can be identified using a satellite-based remote sensing method through interferometry of two SAR images (interferometry synthetic aperture radar or InSAR) uses the Sentinel application platform (SNAP) which is an open source software (FOSS) application. Interferometry can represent changes in the line of sight between the ground and satellites in general. Changes in line of sight can be interpreted as signals of ground deformation. The results of this research can provide adequate information regarding comparative data on land elevation on the Sanga-Sanga Dalam - Pendingin road from several points experiencing land subsidence or deformation on average of 161.3 cm with an average land subsidence rate of 23.04 cm/year . Thus, remote sensing technology using the InSAR technique can be used to determine changes that occur in a short time and at low cost.]]>
<![CDATA[Perbandingan Laju Penurunan Muka Tanah Menggunakan Metode DInSAR dengan Pengolahan Data Aktual ]]>
<![CDATA[Annisa Amelia]]>;
<![CDATA[Nia Kurniadin]]>;
<![CDATA[Romansah Wumu]]>;
<![CDATA[Shabri Indra Suryalfihra]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 2 No. 1 (2023): September 2023 ]]>
Publisher : <![CDATA[Politeknik Pertanian Negeri Samarinda ]]>
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DOI: 10.51967/gets.v2i1.29
<![CDATA[This research is motivated by how the data generated from the capabilities of the radar technology used in monitoring land subsidence using the DInSAR (Differential Interferometry Synthetic Aperture Radar) method is compared with actual data in the mining sector. The purpose of this study was to determine the suitability of the land subsidence rate using the DInSAR method against the actual data. DInSAR processing is carried out using a pair of Sentinel-1 Terrain Observation by Progressive Scans (TOPS) images with acquisition times before and after changes in conditions due to mining activities. Actual data processing in the form of topographical data at the End of the Month (EOM) by carrying out the drape elements process by 30 sample points to provide information on the value of changes in elevation that occur within a period of three months. The results of the research show that there is a discrepancy between the data generated using the DInSAR method and the actual data. This can be due to the limitations of radar sensors in detecting soil dredging activities in mining areas. So that further processing is needed so that the results of Sentinel-1 Image processing with the DInSAR method can represent the value of land subsidence in the field.]]>
<![CDATA[Analisis Spasial Sawah Kabupaten Sidenreng Rappang Menggunakan Data Landsat-8 dengan Metode Random Forest ]]>
<![CDATA[Romansah Wumu]]>;
<![CDATA[Ryo Anugrah]]>;
<![CDATA[Nia Kurniadin]]>;
<![CDATA[Andi Baso Sofyan A. P.]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 2 No. 1 (2023): September 2023 ]]>
Publisher : <![CDATA[Politeknik Pertanian Negeri Samarinda ]]>
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DOI: 10.51967/gets.v2i1.31
<![CDATA[Rice fields play a crucial role in ensuring food security in a region. However, a major challenge is preventing the conversion of rice fields, which can jeopardize food availability. Therefore, it is essential to rapidly and accurately map rice field areas to precisely detect changes. An effective approach involves remote sensing technology and cloud computing. This research aims to map rice fields in Sidenreng Rappang Regency using Landsat-8 data with the random forest method on the Google Earth Engine platform. This method has proven efficient in image classification and yields accurate land mapping. In this study, Landsat-8 data serves as the primary source, with random forest classifying areas as rice fields. The main finding indicates that the total area of rice fields in Sidenreng Rappang Regency reaches 51,480.43 hectares. Validation using data from the Central Statistics Agency (BPS) reveals a difference in area of 0.67%, while regression analysis demonstrates a strong correlation between mapping data and BPS data, with an R-squared value of 0.9455.]]>
<![CDATA[Identifikasi Luasan Banjir Rob di Kota Semarang Pada Tanggal 24 Mei 2022 Menggunakan Citra Landsat ]]>
<![CDATA[Rahman, Andi Nur]]>;
<![CDATA[Kurniadin, Nia]]>;
<![CDATA[Wumu, Romansah]]>;
<![CDATA[Suryalfihra, Shabri Indra]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 1 No. 2 (2023): March 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
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DOI: 10.51967/gets.v1i2.16
<![CDATA[Tidal floods are floods that occur as a result of sea tides that inundate areas that have a lower elevation than sea level. The occurrence of tidal floods is due to sea level rise caused by tides, external forces such as water, wind, or swell (waves caused from a long distance), and storms which are natural phenomena that often occur at sea. A tidal flood in Semarang City on May 23, 2022, occurred with a height of 1.5 meters, occurred in the Tanjung Emas Port area. This tidal flood became the most severe flood in 2022. The utilization of remote sensing technology by using Landsat satellite imagery can be maximized to obtain information about tidal flood events that occurred in the city of Semarang. The purpose of this study was to find out how to identify the area of flooding using Landsat 8 and Landsat 9 imagery using the NDWI method and to determine the extent of the tidal flood that occurred on May 24, 2022, by comparing the wettability values of satellite imagery before and after the tidal flood. The results obtained are in the form of changes in the area of water bodies due to tidal flooding on the north coast of Semarang City in the Tugu sub-district 39.982 Ha; West Semarang 16.765 Ha; North Semarang 5.174 Ha; East Semarang 0.104 Ha; and Genuk 33.393 Ha.]]>
<![CDATA[Analisis Spasial Temporal Klorofil-a Perairan Ponelo Kepulauan Provinsi Gorontalo Tahun 2018-2022 Menggunakan Data Landsat 8 ]]>
<![CDATA[Wumu, Romansah]]>;
<![CDATA[Kurniadin, Nia]]>;
<![CDATA[Suryalfihra, Shabri Indra]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 1 No. 2 (2023): March 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
Show Abstract
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DOI: 10.51967/gets.v1i2.17
<![CDATA[Indonesia's maritime area covers approximately 3.25 million km2, which means that 70% of Indonesia's total area is comprised of the ocean. This indicates the enormous potential that Indonesia's ocean holds. The ocean is a crucial resource for the Ponelo Islands community, whose main livelihood is fishing. The marine ecosystem is vulnerable to environmental changes and pollution. Chlorophyll-a can serve as an indicator of the health of marine waters. Mapping the distribution of chlorophyll-a on the ocean's surface can be achieved through remote sensing technology. The study utilized the Nuriya Algorithm (2010) to derive the chlorophyll-a content in surface waters using Landsat-8 data from 2018-2021. Data processing is done through Google Earth Engine (GEE) which has the ability to process large amounts of data quickly (Big Data). The findings indicate an increase in chlorophyll-a content in the waters of Ponelo Islands at the beginning (DOY 0-20) and end (DOY 300-325) of the year. On a spatial scale, the average chlorophyll-a is widely distributed in the waters of Ponelo but is more concentrated in the coastal areas. This indicates that coastal areas of the Ponelo Islands may be more vulnerable to pollution and environmental changes and require special attention in environmental management and marine ecosystem conservation efforts.]]>
<![CDATA[Analisis Deformasi Jalan Penghubung Antara Kelurahan Sanga-Sanga Dalam dan Kelurahan Pendingin Tahun 2015 dan 2021 Menggunakan Metode Interferometry Synthetic Aperture Radar ]]>
<![CDATA[Muslim, Taufan Yanuar]]>;
<![CDATA[Kurniadin, Nia]]>;
<![CDATA[Widyasasi, Dyah]]>;
<![CDATA[Wumu, Romansah]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 2 No. 1 (2023): September 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
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DOI: 10.51967/gets.v2i1.28
<![CDATA[The rise of coal mining in the East Kalimantan area which is close to public road access is thought to affect the quality and sustainability of surrounding public road access. The aim of this research is to determine the use of remote sensing data to analyze land subsidence or deformation that occurs on the connecting road between Sanga-Sanga Dalam Village and Pendingin Village, Sanga-Sanga District, Kutai Kartanegara Regency. The method used in this research is quantitative descriptive, namely determining ground deformation on roads obtained by analyzing Sentinel-1 imagery in 2015 and Sentinel-1 imagery in 2021. Ground deformation can be identified using a satellite-based remote sensing method through interferometry of two SAR images (interferometry synthetic aperture radar or InSAR) uses the Sentinel application platform (SNAP) which is an open source software (FOSS) application. Interferometry can represent changes in the line of sight between the ground and satellites in general. Changes in line of sight can be interpreted as signals of ground deformation. The results of this research can provide adequate information regarding comparative data on land elevation on the Sanga-Sanga Dalam - Pendingin road from several points experiencing land subsidence or deformation on average of 161.3 cm with an average land subsidence rate of 23.04 cm/year . Thus, remote sensing technology using the InSAR technique can be used to determine changes that occur in a short time and at low cost.]]>
<![CDATA[Perbandingan Laju Penurunan Muka Tanah Menggunakan Metode DInSAR dengan Pengolahan Data Aktual ]]>
<![CDATA[Amelia, Annisa]]>;
<![CDATA[Kurniadin, Nia]]>;
<![CDATA[Wumu, Romansah]]>;
<![CDATA[Suryalfihra, Shabri Indra]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 2 No. 1 (2023): September 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
Show Abstract
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DOI: 10.51967/gets.v2i1.29
<![CDATA[This research is motivated by how the data generated from the capabilities of the radar technology used in monitoring land subsidence using the DInSAR (Differential Interferometry Synthetic Aperture Radar) method is compared with actual data in the mining sector. The purpose of this study was to determine the suitability of the land subsidence rate using the DInSAR method against the actual data. DInSAR processing is carried out using a pair of Sentinel-1 Terrain Observation by Progressive Scans (TOPS) images with acquisition times before and after changes in conditions due to mining activities. Actual data processing in the form of topographical data at the End of the Month (EOM) by carrying out the drape elements process by 30 sample points to provide information on the value of changes in elevation that occur within a period of three months. The results of the research show that there is a discrepancy between the data generated using the DInSAR method and the actual data. This can be due to the limitations of radar sensors in detecting soil dredging activities in mining areas. So that further processing is needed so that the results of Sentinel-1 Image processing with the DInSAR method can represent the value of land subsidence in the field.]]>
<![CDATA[Analisis Spasial Sawah Kabupaten Sidenreng Rappang Menggunakan Data Landsat-8 Dengan Metode Random Forest ]]>
<![CDATA[Wumu, Romansah]]>;
<![CDATA[Anugrah, Ryo]]>;
<![CDATA[Kurniadin, Nia]]>;
<![CDATA[Sofyan A. P., Andi Baso]]>
<![CDATA[ Journal of Geomatics Engineering, Technology, and Science Vol. 2 No. 1 (2023): September 2023 ]]>
Publisher : <![CDATA[P3KM Politani Samarinda ]]>
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DOI: 10.51967/gets.v2i1.31
<![CDATA[Rice fields play a crucial role in ensuring food security in a region. However, a major challenge is preventing the conversion of rice fields, which can jeopardize food availability. Therefore, it is essential to rapidly and accurately map rice field areas to precisely detect changes. An effective approach involves remote sensing technology and cloud computing. This research aims to map rice fields in Sidenreng Rappang Regency using Landsat-8 data with the random forest method on the Google Earth Engine platform. This method has proven efficient in image classification and yields accurate land mapping. In this study, Landsat-8 data serves as the primary source, with random forest classifying areas as rice fields. The main finding indicates that the total area of rice fields in Sidenreng Rappang Regency reaches 51,480.43 hectares. Validation using data from the Central Statistics Agency (BPS) reveals a difference in area of 0.67%, while regression analysis demonstrates a strong correlation between mapping data and BPS data, with an R-squared value of 0.9455.]]>
