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All Journal Jurnal Pendidikan Geografi Undiksha Media Komunikasi FPIPS Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian JPG (Jurnal Pendidikan Geografi) JURNAL ILMIAH GEOMATIKA MAJALAH ILMIAH GLOBE WIDYA LAKSANA Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
A Sediyo Adi Nugraha
Universitas Pendidikan Ganesha
Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Perbandingan Metode Soil Adjusted Vegetation Index (SAVI) dan Forest Canopy Density (FCD) untuk Identifikasi Tutupan Vegetasi (Kasus; Area Pembuatan Jalan Baru Singaraja-Mengwi) Adi Nugraha, A Sediyo; Ananda Citra, I Putu
Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Vol 18, No 1 (2021)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jg.v18i1.25367

Abstract

This research uses Landsat 8 OLI/TIRS image which objective to determine the accuracy level of SAVI method and FCD model in the identification of vegetation cover. It is done as an effort to assist in determining the right method of monitoring the change of vegetation cover in the forest area. Therefore, this research compares the vegetation index of Soil Adjusted Vegetation Index (SAVI) because it is able to suppress the background of the soil so that the vegetation cover is able to be displayed according to the conditions in the field. While the FCD model uses four variables such as; Advanced Vegetation Index (AVI), Bare Soil Index (BI), Shadow Index (SI), and thermal index using the Split-Windows Algorithm (SWA) method. Comparison results between SAVI and FCD models indicate that the higher accuracy of SAVI is 84% and FCD model is only 82%. It is possible because the limited use of research areas that show SAVI is superior due to heterogeneous conditions and it approaches the conditions in the field than the FCD model that is more group and only able to be realized in three classes. Based on the results, it was concluded that the vegetation index can be used in monitoring the limited area of research but it is also not absolute because it is possible that FCD model is better.
Perbandingan Metode Supervised Classification dan Unsupervised Classification terhadap Penutup Lahan di Kabupaten Buleleng Septiani, Rosi; Citra, I Putu Ananda; Nugraha, A Sediyo Adi
Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Vol 16, No 2 (2019)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jg.v16i2.19777

Abstract

Penelitian ini dilaksanakan di Kabupaten Buleleng menggunakan citra Landsat 8 OLI/TIRS (Operational Land Imager/ Thermal Infrared Sensor), dengan tujuan untuk (1) mendeskripsikan metode supervised classification terhadap klasifikasi penutup lahan, (2) mendeskripsikan metode unsupervised classification terhadap klasifikasi penutup lahan, dan (3) membandingkan tingkat akurasi metode supervised classification dengan unsupervised classification terhadap klasifikasi penutup lahan. Metode yang digunakan yaitu metode komparatif dengan membandingkan metode supervised classification dengan unsupervised classification terhadap penutup lahan di Kabupaten Buleleng. Hasil penelitian menunjukkan bahwa (1) diperoleh delapan kelas penutup lahan pada metode supervised classification yang ditentukan oleh pengambilan training area, (2) diperoleh delapan kelas penutup lahan pada metode unsupervised classification yang ditentukan dengan memberikan nilai range statistik, dan (3) tingkat akurasi yang tertinggi dimiliki oleh metode supervised classification yaitu maximum likelihood dengan nilai overall accuracy sebesar 92% dibandingkan dengan metode unsupervised classification (k-means dan ISODATA) yang memiliki nilai overall accuracy yaitu 82,07%. Kesimpulannya adalah untuk deteksi klasifikasi penutup lahan metode yang paling baik dilakukan di Kabupaten Buleleng yaitu supervised classification dengan metode maximum likelihood.This study was conducted in Buleleng Regency using Landsat 8 OLI/TIRS imagery (Operational Land Imager/ Thermal Infrared Sensor), with the aim of (1) describing the supervised classification method for land cover classification, (2) describe the method of unsupervised classification on the classification of land cover, and (3) compare the level of accuracy of the supervised classification method and unsupervised classification on the classification of land cover. The method used is a comparative method  by comparing the supervised classification method with unsupervised classification of land cover in Buleleng Regency. The results showed that (1) eight land cover classes were obtained in the supervised classification method determined by the taking of the training area, (2) eight land cover classes were obtained in the unsupervised classification method determined by providing statistical range values, and (3) the accuracy level the highest is owned by the supervised classification method, namely maximum likelihood with the overall accuracy value of 92% compared to the unsupervised classification method (k-means and ISODATA) which has the overall accuracy value of 82,07%. The conclusion is that the detection of land cover classification method that is best done in Buleleng Regency is the supervised classification with the maximum likelihood method.
Monitoring Perubahan Garis Pantai Di Kabupaten Jembrana Tahun 1997 – 2018 Menggunakan Modified Difference Water Index (Mndwi) Dan Digital Shoreline Analysis System (DSAS) Muhammad Zainul Hasan; I Putu Ananda Citra; A Sediyo Adi Nugraha
Jurnal Pendidikan Geografi Undiksha Vol. 7 No. 3 (2019): Jurnal Pendidikan Geografi Undiksha
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jjpg.v7i3.21507

Abstract

Penelitian ini bertujuan untuk menerapkan metode Modified Difference Water Index (MNDWI) untuk mempertegas batas antaradaratan dan perairan serta menganalisis perubahan garis pantai di Kabupaten Jembrana tahun 1997-2018 menggunakan Digital Shoreline Analysis System (DSAS). Metode perhitungan yang digunakan pada DSAS yaitu Net Shoreline Movement dan End Point Rate. Pengamatan perubahan garis pantai mengambil rentang waktu selama 21 tahun menggunakan citra Landsat tahun 1997, 2008 dan 2018. Hasil penelitian menyebutkan Nilai MNDWI yang lebih besar dari nol diasumsikan sebagai badan air dan jika lebih kecil dari nol akan diasumsikan sebagai daratan. Tingkat abrasi tertinggi pada tahun 1997 - 2008 terjadi di Desa Delodberawah sebesar 132,94 m dengan laju abrasi pertahunnya sebesar 12,085. Tingkat akresi tertinggi pada periode ini terjadi secara masif di Desa Pengambengan sebesar 582,87 m dan laju akresi pertahunnya 52,988 m. Pada tahun 2008 - 2018 nilai abrasi tertinggi meningkat menjadi 254,41 m dengan laju abrasi sebesar 25,441 m yang terjadi di Desa Perancak. Sedangkan  nilai akresi pada periode ini mengalami penurunan, dengan tingkat akresi tertinggi sebesar 287,08 m dan laju akresi sebesar 28,708 m yang terjadi di Desa Pengambengan
Kondisi Sosial Dan Ekonomi Masyarakat Pengungsi Bencana Erupsi Gunung Agung Desa Ban I Gede Putu Suarjana; Putu Indra Christiawan; A Sediyo Adi Nugraha
Jurnal Pendidikan Geografi Undiksha Vol. 8 No. 1 (2020): Jurnal Pendidikan Geografi Undiksha
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jjpg.v8i1.23475

Abstract

Penelitian ini bertujuan untuk mengetahui kondisi sosial dan ekonomi masyarakat pengungsi Desa Ban, Kecamatan Kubu, Kabupaten Karangasem KRB III radius 6 Km selama mengungsi dan pasca mengungsi. Penelitian ini mengunakan metode analisis kualitatif dan bidang ilmu yang digunakan untuk mengkaji yaitu geografi penduduk yang dianalisis dengan pendekatan keruangan. Sampel wilayah diambil di Desa Ban meliputi empat dusun yaitu Dusun Belong, Dusun Cegi, Dusun Pengalusan dan Dusun Pucang. Sampel diambil sejumlah 110 orang yang ditentukan dengan proporsional random sampling. Pengumpulan data menggunakan metode observasi, wawancara, dan studi pustaka. Hasil penelitian menunjukkan bahwa masyarakat Desa Ban yang masuk KRB III radius 6 Km selama mengungsi kondisi sosial terkategori sedang yaitu sebanyak 67%, pasca mengungsi kondisi sosial masyarakat terkategori baik yaitu sebanyak 66% dan selama mengungsi kondisi ekonomi masyarakat terkategori sedang yaitu sebanyak 45%, pasca mengungsi kondisi ekonomi masyarakat terkategori baik yaitu sebanyak 71%. Selama mengungsi kerjasama di buktikan dengan kompak masyarakat pengungsi dalam bergotong royong membersihkan posko pengungsian namun tidak dilakunan setiap hari, konflik kadang terjadi karena kesalahpahaman antar masyarakat pengungsi maupun masyarakat lokal sekitar posko pengungsi dan pasca mengungsi kerjasama makin kompak dan konflik tidak pernah terjadi karena rasa kekeluargaan makin erat. Kondisi ekonomi selama mengungsi dikatakan sedang di buktikan dengan masyarakat yang bekerja sebagai petani dan buruh tidak bisa bekerja lain halnya dengan masyarakat Desa Ban yang menjadi pegawai kontrak maupun PNS masih bisa bekerja dan pendapatannya tetap namun pasca mengungsi masyarakat sudah bisa bekerja seperti bisa dan mendapatkan pendapatan yang cukup.
Tipe Pengangguran Terdidik: Antara Setengah Menganggur dan Terselubung pada Alumni Prodi Pendidikan Geografi Undiksha Tahun 2017-2019 Ni Made Sri Sudarmi; I Made Sarmita; A Sediyo Adi Nugraha
Jurnal Pendidikan Geografi Undiksha Vol. 8 No. 3 (2020): Jurnal Pendidikan Geografi Undiksha
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jjpg.v8i3.29214

Abstract

Penelitian ini bertujuan untuk menganalisis tipe pengangguran pada alumni Program Studi Pendidikan Geografi Undiksha tahun 2017-2019. Subjek penelitian menggunakan studi populasi yaitu alumni Program Studi Pendidikan Geografi Undiksha yang diwisuda tahun 2017-2019. Pengumpulan data dalam penelitian ini menggunakan metode wawancara dan kuisioner yang selanjutnya dianalisis secara deskriptif kualitatif. Hasil penelitian menunjukkan bahwa tipe pengangguran yang dialami alumni Program Studi Pendidikan Geografi Undiksha tahun 2017-2019 meliputi tipe pengangguran terbuka sebesar 6%, tipe setengah menganggur sebesar 14,3%, tipe pengangguran terselubung sebesar 51% dan tipe pengangguran musiman sebesar 6%. Tipe pengangguran yang paling mendominasi adalah tipe setengah menganggur dan tipe pengangguran terselubung. Tipe setengah menganggur yang terjadi pada alumni disebabkan oleh faktor tempat kerja yang terbatas sebanyak 12,9% dan jam kerja yang pendek sebanyak 9,7%, sedangkan penyebab timbulnya tipe pengagguran terselubung disebabkan oleh faktor minimnya lowongan kerja sebesar 38,7% dan faktor saingan sebesar 19,3%. 
Application of Remote Sensing Data for Slum Identification Using Geography Information System (Case: Former Harbor, Singaraja City) Ruhilatul Janah; A Sediyo Adi Nugraha
Media Komunikasi FPIPS Vol. 20 No. 1 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkfis.v20i1.30421

Abstract

This research was conducted in Singaraja City using high-resolution remote sensing images and geographic information systems. The purpose is to use remote sensing images and geographic information systems to identify slum settlements, especially the former harbor area in Singaraja City. Slum settlement is the impact of population growth that is difficult to control. As a result, the remote sensing image can identify three features: slums, non-slum settlement, and non-slum areas. Most slum settlements are located in coastal areas, and non-slum settlements are located in areas close to economic locations and tourist sites and offices. The most significant introduction to slum identification comes from the building area. Based on these results, it can be concluded that slum settlement can be identified through images obtained from Google earth and recognized visually through interpretation keys. 
Normalized Dryness Built-up Index (NDBI) to Detect Settlement Change In Buleleng Sub-District Muhammad Rahman; A Sediyo Adi Nugraha
Media Komunikasi FPIPS Vol. 20 No. 1 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkfis.v20i1.30427

Abstract

This research aims to find out the development of settlements that occur over the next 20 years. Monitoring the development of settlements is carried out by remote sensing methods using Landsat 7 ETM+ imagery and Landsat 8 OLI imagery. Landsat 7 ETM+ used in 2000, and Landsat 8 OLI used in 2019. The algorithm is used to identify settlement development using the Normalized Dryness Built-up Index (NDBI). This algorithm uses two bands, such as Near-infrared and shortwave infrared, to calculate. The results showed that the growth of settlements occurred very significant because, in 2000, the number of settlements amounted to 628.2 hectares and in 2019 amounted to 1891.8 hectares. The increase in settlements occurred throughout the region in the Buleleng sub-district. Therefore, it can be concluded that NDBI can be used to monitor the development of settlements and the increase in settlements occurring as much as 28 % over 20 years.
The Application of Landsat 8 OLI to Identification Shoreline Change in 2000 – 2020 in Muncar Sub-District, Banyuwangi, East Java Lutfiatul Janah; A Sediyo Adi Nugraha; Restu Ade Yanti; Lilis Nuraini
Media Komunikasi FPIPS Vol. 21 No. 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkfis.v21i1.42585

Abstract

The shoreline is a confluence between land and seawater used to determine the boundaries of a zone. This research was conducted on the coastline of Muncar Subdistrict, Banyuwangi, which aims to identify changes in the coastline of Muncar Subdistrict in 2000-2020 using Landsat image 8 OLI / TIRS, map the rate of changes in the coastline of Muncar Subdistrict in 2000 and 2020, and know the changes in the coastline in Muncar Subdistrict is more likely due to abrasion or accretion. The research methodology used for this study uses the NDVI analysis and the DSAS Shoreline analysis system. The identification takes 20 years with Landsat imaging in 2000 and 2020. The results of this study demonstrate that shoreline alterations are caused by abrasion, accretion and human activity. This change in shoreline results from abrasion and accretion factors. The coastline change in 2000-2020 in the subdistrict of Muncar can be concluded that there are six villages. These include the villages of Kumendung, Sumbersewu, Tembokrejo, Kedungrejo, Kedungwringin and Wringin Putih. However, the village most seriously affected by abrasion and accretion is Wringim Putih Village. The village of Wringin Putih reported that the level of abrasion and accretion could be considered 50 per cent abrasion and 50 per cent accretion. So the change in shoreline can result around the Muncar Subdistrict coastal area, such as reduced coastal areas, lost colonies, and damage to marine ecosystems
Comparison Normalized Dryness Built-Up Index (NDBI) with Enhanced Built-Up and Bareness Index (EBBI) for Identification Urban in Buleleng Sub-District Lilis Nuraini; A Sediyo Adi Nugraha; Restu Ade Yanti; Lutfiatul Janah
Media Komunikasi FPIPS Vol. 21 No. 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkfis.v21i1.43007

Abstract

The research aims to determine how much accuracy is improved in developing settlements and distinguish the areas built up and vacant land in Buleleng, Bali district. This study used remote sensing methods to monitor and detect changes in the waking area using Landsat 8 OLI imagery.  Identify settlement developments using the Normalized Difference Built-up Index (NDBI) and Enhanced Built-Up and Bareness Index (EBBI) algorithms. Both algorithms use red and infrared bands as the basis for identifying building differences. As a result, NDBI and EBBI have differences where the accuracy of EBBI is higher than NDBI by 84% and 82%. The difference in accuracy is influenced by the appearance of vegetation and clay-roofed buildings. Based on that, it can be concluded that in identifying the building, EBBI has a higher capacity compared to NDBI, but it must be ensured that in the use of EBBI, the area studied has a more dominant appearance of the building.
Identification of the Actual Shoreline Impact on Pond With ArcGIS Basemap Images In Muncar Sub-District, Banyuwangi Regency Restu Ade Yanti; A Sediyo Adi Nugraha; Lutfiatul Jannah; Lilis Nuraini
Media Komunikasi FPIPS Vol. 21 No. 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkfis.v21i1.43008

Abstract

The regulatory law no. 32 of article 14 of 1990 is regulated at least 100 meters calculated from the highest tidal point towards the continent. Pond use must consider the distance from the shoreline to avoid losses. This research aims to discover the coastline influence on the sustainability of the ponds in the Muncar Sub-district. The methodology used in this study was digitized on the screen using the ArcGIS base map. The existence of a coastline in digitization for determining an area occurs abrasion or accretion. Then the pond is digitized to discover its existence, then computes the length of the shoreline. The results obtained the existence of the coastline that there are ponds along 15,907.87 m and no pond shoreline 8,173.02 m. In comparison, the number of working ponds can reach 247 plots. Among the five villages that have ponds, three have complied with the regulations. The Kumendung Village is 1432 meters, Sumbersewu Village is 336 meters, Kedungwringin Village is 857 meters eligible, and the other two villages are ineligible Tembokrejo Village along 5 meters and Wringinputih Village 7.3 meters. Ponds that do not comply with regulations are exposed to an abrasion hazard. Therefore, there need to be countermeasures such as backfilling or mangrove planting. Based on these findings, observations should be made to discover the truth of the shoreline existence against ponds that are at risk of abrasion.
Co-Authors Arrasyid, Riko Dewa Made Atmaja Hasan, Muhammad Zainul I Gede Putu Suarjana I Made Sarmita I Putu Ananda Citra I Putu Ananda Citra Ida Bagus Made Astawa Janah, Ruhilatul Lilis Nuraini Lutfiatul Janah Lutfiatul Jannah Muhammad Rahman Muhammad Zainul Hasan Ni Made Sri Sudarmi Putu Indra Christiawan Rahman, Muhammad Restu Ade Yanti Ridwana, Riki Ruhilatul Janah Septiani, Rosi Setio Galih Mariyono Shafira Himayah, S.Pd., M.Sc. Suarjana, I Gede Putu Sudarmi, Ni Made Sri Yuda Aulia Aziz