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Kajian dan Evaluasi Bencana Tanah Longsor di Kecamatan Tanjungsari terhadap RTRW Kabupaten Bogor Sri Fauza Pratiwi; Masita Dwi Mandini Manessa; S Supriatna
Jurnal Wilayah dan Lingkungan Vol 10, No 1 (2022): April 2022
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jwl.10.1.86-96

Landslide is one of the natural disasters that often occurs in Indonesia, which has various geographical conditions and different topography of different areas. Landslide is one of the natural disasters that often occurs in Indonesia as a country that has various geographical conditions and different topography of different areas. However, an exhaustive study of spatial use which includes suitability assessment between the Regional Spatial Plan (Rencana Tata Ruang Wilayah/RTRW) documents and regional potential and other factors such as disasters is still rarely carried out. Tanjungsari District, Bogor Regency is an area that has experienced landslides in January 2020. The purpose of this study was to evaluate the RTRW of Bogor Regency against landslides in Tanjungsari District. The vulnerability of a site to landslides is caused by several factors which are used as parameters in this study. The parameters are land use, rainfall, slope, geology, and soil type. Each parameter used is given a score and weight then an overlay of each parameter weighting is carried out to obtain a landslide susceptibility map. Furthermore, a descriptive spatial analysis of the landslide hazard was carried out on the spatial plan of the Bogor Regency. The results when compared with the existing conditions, the use of plantation land and forest areas overlap with areas prone to landslides. Thus, it is necessary to review the existing RTRW maps to reduce the impact of landslides.

CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City Supriatna Supriatna; Mutia Kamalia Mukhtar; Kartika Kusuma Wardani; Fathia Hashilah; Masita Dwi Mandini Manessa
Indonesian Journal of Geography Vol 54, No 3 (2022): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.71721

Land cover change is a prevalent thing in Indonesia. This phenomenon often causes deforestation rates to continue to increase every year, which can cause various natural disasters. This study will look at changes in land cover, make land cover prediction models, and see the relationship between land cover changes and the flood disaster that occurred in Banjarmasin City and its surroundings. Remote sensing is used to see changes in land cover from year to year with GlobeLand30 satellite imagery. Satellite imagery processing is carried out using the Cellular Automata – Markov Chain method to see the land cover prediction. The results show that the most significant land cover change from 2000 to 2020 is experienced by built-up land and forests, while in 2030, forests are predicted to experience deforestation of 356 km2 from 2020. The deforestation will cause catastrophic flooding in 2021, where flooding extends to areas that are not estimated to be high flood hazards, with 111 flood points located in the plantation area.

ANALISIS SPASIAL DAERAH POTENSI RAWAN LONGSOR DI KOTA AMBON DENGAN MENGGUNAKAN METODE SMORPH Heinrich Rakuasa; S Supriatna; Mangapul Parlindungan Tambunan; Melianus Salakory; Wiclif. S. Pinoa
Jurnal Tanah dan Sumberdaya Lahan Vol. 9 No. 2 (2022)
Publisher : Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

The geographical condition of Ambon City, which is 75% a hilly area resulted in most communities building in marbled areas with slopes above 20%, which has the potential to threaten life and landslide disasters. This study simply looked at the influence of slopes and slope shapes in Ambon City that can be analyzed using geographic information systems (GIS) to map areas that have the potential for landslides. Identification and mapping of potential landslide areas have an important role as an effort in overcoming and anticipating the occurrence of landslide disasters. This study aimed to analyze the spread of potential landslide areas in Ambon City based on the results of SMORPH modeling. The study used the slope morphology or SMORPH method, which has a better degree of accuracy than the Storie Index and SINMAP methods to identify and classify potential landslide areas based on the matrix between slope shape and slope angle. This study resulted in 4 levels of landslide potential areas, namely very low, low, medium and high potential. Areas with high landslide potential dominate the northern and southern parts of Ambon City. In the region, most landslides occur in the form of sunken and convex slopes. The region has a hilly and mountainous topography with a steep slope. The results of this research using the SMORPH method can illustrate that the slope of the increasingly higher slope accompanied by the shape of a convex or concave slope will cause the potential for landslides that are higher in the region.

Spatial Distribution of Coral Reef Degradation with Human Activities in the Coastal Waters of Samatellu Lompo Island, South Sulawesi Muhammad Rafi Andhika Pratama; Masita Dwi Mandini Manessa; Supriatna Supriatna; Farida Ayu; Muhammad Haidar
Geoplanning: Journal of Geomatics and Planning Vol 9, No 2 (2022)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.9.2.121-132

A healthy coral reef ecosystem can be beneficial for the survival of fish habitats and aquatic ecosystems. This study aims to analyze the influence of human activities on the spatial distribution of coral reefs in the coastal waters of Samatellu Lompo Island, Pangkajene Islands Regency, South Sulawesi in 2000, 2014, 2018, and 2021. The spatial distribution of coral reefs was obtained through a field survey using the underwater transect photo method. Then, satellite images were processed by using the Lyzenga algorithm for water column correction, and aquatic objects were classified by using unsupervised classification. Human activities that affect coral reef destruction were obtained through interviews and it was strengthened with related literature studies. The results showed that the coral reefs in the coastal waters of Samatellu Lompo decreased from 2000-2021. In 2000, the live coral area was 13.53 ha, whereas in 2021 it was 8,031 ha. Destructive fishing activities such as using bombs and poison in catching fish are the main factors of coral reef destruction. In addition, destructive fishing activities commonly occur in the western and northern waters of Samatellu Lompo that causing the live coral into dead coral or rubble.

Pemodelan Dampak Perubahan Iklim dan WIUP terhadap Potensi Habitat Burung Walik Benjol di Pulau Obi Kartika Pratiwi; Supriatna Supriatna; Masita Dwi Mandini Manessa; Aris Poniman K; Mangapul P. Tambunan
Jurnal Serambi Engineering Vol 8, No 1 (2023): Januari 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i1.5571

AbstractOne of the impacts of climate change is the degradation quality of natural habitats of flora and fauna in Indonesia, risking the loss of most of the existing biodiversity. Obi Island as a natural habitat for several endemic species cannot be avoided from the threat of climate change impacts. The existence of mining concessions also can have a direct impact on their habitat potential. The purpose of this study was to analyze the distribution pattern of endemic species under current climatic conditions, synthesize models of the impact of climate change and analyze mining concessions on the distribution of potential habitats of Carunculated Fruit-dove on Obi Island. The occurrence data of Carunculated Fruit-dove and 19 bioclimatic variables are used as input in the process of making a habitat model with MaxEnt. As a result, the habitat potential model of Carunculated Fruit-dove with AUC = 0.955 has a very suitable habitat potential with an area of 66.02 km2 or 2.68%. The climate change in 2041-2060 with 4 different climate scenarios has an impact on the Carunculated Fruit-dove habitat potential model. Mining Business Permit Areas on Obi Island that have been issued until March 2022 amount to 19 locations with a total area of 373.14 km2 which will have a direct or indirect impact on the potential habitat of Carunculated Fruit-dove on Obi Island. 14.17 km2 of 66.67 km2 of potential habitat that is very suitable for Carunculated Fruit-dove will be directly affected by the existence of these mining areas.Keywords: endemic species, mining business permit area, climate change, obi island, maximum entropy

Identification of Landslide Prone Areas Using Slope Morphology Method in South Leitimur District, Ambon City Nadhi Sugandhi; Supriatna Supriatna; Heinrich Rakuasa
Jambura Geoscience Review Vol 5, No 1 (2023): Jambura Geoscience Review (JGEOSREV)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jgeosrev.v5i1.14810

South Leitimur District is one of the districts in Ambon City where landslides often occur, and this disaster causes many losses. One of the mitigation efforts is mapping areas with the potential for landslides to determine their distribution and risks. This study aims to apply the slope morphology method to identify landslide-prone areas in South Leitimur Regency. This study uses a Digital Elevation Model (DEM) extracted into the shape of slopes and slopes and processed using ArcGIS 10.8 software. This study uses the slope morphology method or SMORPH to identify and classify areas with potential landslides based on the matrix between the slope's shape and angle. The results of the study were classified into four classes of landslide potential, namely very low potential with an area of 2,489, 53 ha, low with an area of 3,278, 22 ha, medium with an area of 672, 32 ha, and high with an area of 685, 67 ha. Hutumury Village is a village that has the largest landslide potential area in each class of landslide potential in the South Leitimur District; this is because this village is a village that has the most significant area compared to other villages. The village that has a low landslide potential is Ema Village. The results of this study also illustrate that the higher the slope with convex or concave slopes, the higher the potential for landslides. The results of this study are expected to help the government of South Leitimur Regency in efforts to mitigate landslides in the future.

Dinamika Total Suspended Solid (TSS) Berdasarkan Citra Landsat 8 Oli Pada Alur Pelayaran Pelabuhan Patimban, Subang, Jawa Barat I Gede Yussupiartha Sas Tangeb; Supriatna Supriatna; Widodo Setiyo Pranowo
Jurnal Kelautan Nasional Vol 18, No 2 (2023): AGUSTUS
Publisher : Pusat Riset Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/jkn.v18i2.12628

Total Suspended Solid (TSS) atau Total Padatan Tersuspensi merupakan padatan atau bahan-bahan yang tersuspensi dengan diameter > 1 μm yang ukuran maupun beratnya lebih kecil daripada sedimen lainnya misalnya tanah liat, bahan-bahan organik tertentu, sel-sel mikroorganisme, jasad-jasad renik, lumpur, pasir halus dan sebagainya yang disebabkan oleh kikisan tanah yang terbawa ke badan air. Dalam kegiatan pelayaran, sedimentasi yang terjadi dapat berpengaruh terhadap keselamatan bernavigasi bagi kapal – kapal, khususnya yang melintas di alur pelayaran. Penggunaan citra satelit dalam pemantauan sebaran konsentrasi TSS memiliki keuntungan yaitu luasnya jangkauan wilayah yang dapat terekam guna mendapatkan detail informasi dan data yang menjadi bahasan pengkajian. Tujuan dari penelitian ini adalah menganalisis dinamika konsentrasi TSS berdasarkan hasil pengukuran, serta menguji beberapa algoritma untuk menduga TSS di perairan Patimban guna mendapatkan algoritma TSS yang sesuai, sehingga dapat digunakan untuk mengekstraksi nilai TSS dari data citra pada periode yang ditentukan. Metode dalam penelitian ini adalah metode survei, dimana lokasi sampling terdiri dari 21 titik sampling serta menggunakan data citra satelit landsat 8 OLI. Penelitian dilakukan pada bulan Agustus – September 2019. Lokasi penelitian terdiri dari 21 titik secara purposive sampling. Nilai konsentrasi TSS pada insitu memiliki nilai rata-rata konsentrasi sebesar 157,86 mg/l. Nilai konsentrasi TSS dari analisis data citra dihitung menggunakan algoritma Budhiman, Guzman-Santaella dan Parwati, dimana algoritma Syarif Budhiman memiliki nilai koefisien korelasi yang sangat kuat dengan nilai R2=0,9086, sehingga paling cocok untuk selanjutnya dilakukan pengembangan algoritma TSS yang dapat digunakan untuk mengukur konsentrasi TSS di perairan Patimban, Subang, Jawa Barat.

Land cover change analysis in Majalengka Regency using the pan-sharpening method and random forest machine learning algorithm Hari Prayogi; Hafid Setiadi; Supriatna Supriatna; Dewayany Dewayany
Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi Vol 28, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um017v28i22023p178-192

The ever-increasing population has accelerated the need for housing and supporting facilities. Further, this growing number of residences and life support facilities resulted in changes in land cover. For instance, the construction of the West Java International Airport and the increase in the population resulted in land cover changes in Majalengka Regency, Indonesia. This study aims to analyze changes in land cover during 2014, 2018, and 2022 in the Majalengka district using Landsat 8 satellite imagery. We used the pan-sharpening research method, while for the closure classification, we used machine-learning random forest algorithms on the google earth engine platform. The land cover classification classes adopted in this study were natural vegetation, cultivated vegetation, open land, built-up land, and bodies of water. The obtained land cover classification results suggested overall accuracy values of 0.96, 0.94, and 0.93 in 2014, 2018, and 2022 respectively, with kappa index values of 0.950, 0.925, and 0.91667. The results indicate a trend of changes in the land cover in the Majalengka district. From 2014-2022, the trend of increasing land cover area was observed in open land and built-up land, while the decreasing land cover area was found in natural vegetation and cultivated vegetation areas. Using both the pan-sharpening method and the machine learning random forest algorithm, we established images with a more detailed appearance with an outstanding kappa accuracy value (above 0.85). Therefore, the developed algorithm can be used in land cover change mapping analysis.

Age Estimation of Paddy using Sentinel-2 Imagery: A Case Study in Java Island, Indonesia Masita Dwi Mandini Manessa; Supriatna Supriatna; Iqbal Putut Ash Sidik
AGRIVITA Journal of Agricultural Science Vol 45, No 3 (2023)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v41i0.3106

Plant age plays a crucial role in determining rice yield. The study on the prediction model of spatially specific rice plant age was still less reported, especially that based on high spatial resolution multispectral data. This study investigates the use of Geographic Weighted Regression (GWR) and extracted vegetation indexes (VI) from the Sentinel-2 multispectral image to build the prediction model based on the time-series dataset from the paddy field observation station. The GWR result was also compared to the Linear Regression (LR) model to demonstrate the impact of including spatial attribute into the prediction model. Since the majority of paddy field observation stations are situated on Java Island, it served as the research location for this investigation. The results indicate that VI from the Sentinel-2 image shows a significant correlation with the age of the paddy, then the VI was able to use as a predictor to build the paddy age prediction model. In the statistical evaluation of the model, the coefficient of determination values (R2) reached 0.65, and the RMSE of estimate value was 15 days.

Pemodelan Dampak Perubahan Iklim dan WIUP terhadap Potensi Habitat Burung Walik Benjol di Pulau Obi Kartika Pratiwi; Supriatna Supriatna; Masita Dwi Mandini Manessa; Aris Poniman K; Mangapul P. Tambunan
Jurnal Serambi Engineering Vol 8, No 1 (2023): Januari 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i1.5571

AbstractOne of the impacts of climate change is the degradation quality of natural habitats of flora and fauna in Indonesia, risking the loss of most of the existing biodiversity. Obi Island as a natural habitat for several endemic species cannot be avoided from the threat of climate change impacts. The existence of mining concessions also can have a direct impact on their habitat potential. The purpose of this study was to analyze the distribution pattern of endemic species under current climatic conditions, synthesize models of the impact of climate change and analyze mining concessions on the distribution of potential habitats of Carunculated Fruit-dove on Obi Island. The occurrence data of Carunculated Fruit-dove and 19 bioclimatic variables are used as input in the process of making a habitat model with MaxEnt. As a result, the habitat potential model of Carunculated Fruit-dove with AUC = 0.955 has a very suitable habitat potential with an area of 66.02 km2 or 2.68%. The climate change in 2041-2060 with 4 different climate scenarios has an impact on the Carunculated Fruit-dove habitat potential model. Mining Business Permit Areas on Obi Island that have been issued until March 2022 amount to 19 locations with a total area of 373.14 km2 which will have a direct or indirect impact on the potential habitat of Carunculated Fruit-dove on Obi Island. 14.17 km2 of 66.67 km2 of potential habitat that is very suitable for Carunculated Fruit-dove will be directly affected by the existence of these mining areas.Keywords: endemic species, mining business permit area, climate change, obi island, maximum entropy

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