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All Journal Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan MEDIA KOMUNIKASI TEKNIK SIPIL Jurnal Geodesi Undip Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Jurnal Kelautan Tropis Journal of Applied Geospatial Information Elipsoida : Jurnal Geodesi dan Geomatika Jambura Geoscience Review Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat JGISE-Journal of Geospatial Information Science and Engineering Jurnal Surya Masyarakat Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi
Nurhadi Bashit
Department Of Geodetic Engineering – Engineering Faculty – Diponegoro University, Jl. Prof Sudarto, SH, Tembalang, Semarang, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Physics Public Health Social Sciences

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Journal : Journal of Applied Geospatial Information

 1 
Analysis of Built-up Land Spatial Patterns Using Multitemporal Satellite Imagery in Pekalongan City Nurhadi Bashit; Yudo Prasetyo; Abdi Sukmono
Journal of Applied Geospatial Information Vol 4 No 2 (2020): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5.281 KB) | DOI: 10.30871/jagi.v4i2.2014

Abstract

Regional growth is characterized by an increase in built-up land. An increase in built-up land can cause changes in land use such as vacant land turned into built-up land. One of the cities in Central Java that experienced an increase in built-up land was in the City of Pekalongan. Based on Pekalongan City Regulation Number 30 Year 2011, the National Spatial Planning stipulates that Pekalongan City is the Regional Activity Center. This causes the Pekalongan City to have the potential to increase the amount of built-up land. An increase in uncontrolled built-up land can cause negative impacts such as reduced water catchment areas so that the disruption of water resources conditions. Therefore, it is necessary to monitor the increase of built-up land in Pekalongan City and see its development spatial patterns. One of method for monitoring a city's built-up land uses the remote sensing method. This study uses an Index-based Built-up Index (IBI) algorithm. Based on the results of this study, it can be concluded that the city of Pekalongan experienced an increase in built-up land between 2013 and 2019. The largest increase in built-up land is in the range of 2017 to 2019 with an area of increase of 359.088 ha so that it can be obtained the speed of increase of built-up land by 170.544 ha/year. The spatial pattern of built-up land increased in 2017 to 2019 heading south because South Pekalongan Regency has a toll road that connects the main road with the toll road.
Combination of Terrestrial Laser Scanner and Unmanned Aerial Vehicle Technology in The Manufacture of Building Information Model Sawitri Subiyanto; Nurhadi Bashit; Naftalie Dinda Rianty; Aulia Darmaputri Savitri
Journal of Applied Geospatial Information Vol 5 No 2 (2021): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v5i2.3444

Abstract

The rapid development of the construction world in Indonesia has led to an increase in supporting technology that is more effective and efficient. The Building Information Model (BIM) technology that begins with the creation of an as-built 3D model, this model describes the existing condition of the building. The Terrestrial Laser Scanner (TLS) method can provide a point cloud with a decent point density, but there are still areas of the building that aren't covered, such as the roof. To be more complete and detailed, additional data is needed using an Unmanned Aerial Vehicle (UAV). The results of the combination of TLS and UAV complement each other so that the results of the point cloud can form more detailed buildings. BIM may be built by combining these two data sets, allowing for the three-dimensional depiction of assets in buildings. The registration results for TLS point cloud data have a fairly good value where the overlap value is 44.9% (minimum 30%), balance is 41.2% (minimum 20%), points < 6mm is 98.9% (minimum 90%). The measurement results using the UAV have an RMSE GCP value of 0.266m and an RMSE ICP of 0.455m. Merging the results of TLS and UAV measurements is done using 3DReshaper software with four align points. The final result of making the BIM model is obtained level of detail (LOD) 3 where room models such as columns, floors, stairs, and walls are well depicted, while asset models such as furniture are also depicted although they are still simple objects.
Application of Generalized Additive Model for Identification of Potential Fishing Zones Using Aqua and Terra MODIS Imagery Data Bandi Sasmito; Nurhadi Bashit; Bella Riskyta Arinda; Abdi Sukmono
Journal of Applied Geospatial Information Vol 6 No 1 (2022): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v6i1.3962

Abstract

Remote sensing applications can provide information on oceanographic conditions for identification of potential fishing zones by combining statistical approaches. Determination of fish catch zones needs to be studied on the relationship between oceanographic parameters and fish catches to improve the efficiency and effectiveness of fishing operations by fishermen. Based on this, identification of potential fishing zones needs to examine the relationship between fish catches and oceanographic parameters using the Generalized Additive Model (GAM) in the Java Sea. GAM analysis was carried out using fish catch data as response variables and oceanographic parameters such as sea surface temperature (SST) and chlorophyll-a image processing results from MODIS, SSS from CMES, and Depth data as predictor variables. The selection of the best model is determined by the highest percentage of CDE and the lowest AIC. GAM modeling results show that 60.3% of fish catches in the Java Sea are influenced by oceanographic factors and 39.7% by other factors. The oceanographic parameter that has the most influence on fish catches is the concentration of chlorophyll-a. GAM modeling results show that fish in the Java Sea tend to be found in sea that have chlorophyll-a concentrations of 0.2 mg/m3 – 0.5 mg/m3, SST 280C – 310C, salinity 31.8 PSU – 33 PSU, and a depth of 20 m. – 50 meters. Potential fishing zones were identified based on the results of the GAM modeling analysis. Potential fishing zones in the Java Sea from March 2021 to June 2021 have varying spatial distributions. The results of the most fishing potential zones were found on June 3, 2021, which were distributed the most in the sea around Pulau Laut, in the southern part of the island of Borneo, and the north on the island of Madura.
Co-Authors Abdi Sukmono, Abdi Abdul Syakur Adri Panjaitan Ahmad Shofiyul Huda Aisah Hajar Alfi Dian Ranu Wijaya Andri Suprayogi Arief Laila Nugraha Arwan Putra Wijaya Aulia Darmaputri Savitri Aulia Fikki Wicaksono Aysha Puspa Pertiwi Bambang Darmo Yuwono Bambang Sudarsono Bandi Sasmito BASKORO AGUM GUMELAR Baskoro Agum Gumelar Bella Riskyta Arinda Bilal Fadhlurrohman Billy Silaen Destya Ulfiana Desyta Ulfiana Devi Irsanti Dicky Nur Krisnha Ertha Silalahi Faradina Sekar Melati Farhan Ardianzaf Putra Farouki Dinda Rassarandi Fauzi Janu Amarrohman, Fauzi Janu Firman Hadi Galih Pratiwi Gantra S.D Hutahaean Grandy Loranessa Wungo Hana Sugiastu Firdaus Haniah Haniah Hanum Fadhil Baihaqi Hanum Fadhil Baihaqi Hardi Wibowo Hot Parningotan Banjarnahor I Komang Ary Sukma Putra Iqbal Yukha Nur Afani Jonathan Ardian Hendra Pranoto Kurniawan Teguh Martono Laode M Sabri Lia Novianti Ni’amah LM Sabri Moehammad Awaluddin Muhammad Asadullah Al Fathin Naftalie Dinda Rianty Naufal Farras Novia Sari Ristianti Novia Sari Ristianti Novia Sari Ristianti Novitasari Novitasari Nurrabia Fitriani Restu Fadilla Risa Bruri Utami Risqi Fadly Robby Sawitri Subiyanto SELLI ANGELITA BR SITEPU Selli Angelita Sitepu Sintauli Manullang Siti Susanti Syarifah Mayda Az Zahrotun Nisa Thia Prahesti Thia Prahesti Titis Ismayanti Trevi Austin Rajagukguk TREVY AUSTIN RAJAGUKGUK Wahyu Setianingsih Welman Manuel Sitorus Widi Wicaksono Yasser Wahyuddin Yasser Wahyudin Yudi Eko Windarto Yudo Prasetyo Zulfaidah Ariany