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All Journal Jurnal Teknologi Perikanan dan Kelautan Marine Fisheries: Jurnal Teknologi dan Manajemen Perikanan Laut Jurnal Ilmu dan Teknologi Kelautan Tropis Jurnal Ilmu-Ilmu Perairan dan Perikanan Indonesia AGRISAINS JURNAL ILMIAH PLATAX ILMU KELAUTAN: Indonesian Journal of Marine Sciences Jurnal Perencanaan Wilayah dan Kota Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Journal of Applied Geospatial Information AGRIKAN Jurnal Ilmiah Agribisnis dan Perikanan Jurnal Penelitian Pengelolaan Daerah Aliran Sungai Bawal : Widya Riset Perikanan Tangkap Jurnal Kelautan Nasional Jurnal Segara Jurnal Sosial Ekonomi Kelautan dan Perikanan Jurnal Iktiologi Indonesia (Indonesian Journal of Ichthyology) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Setyo Budi Susilo
Departemen Ilmu Dan Teknologi Kelautan, Fakultas Perikanan Dan Ilmu Kelautan, Institut Pertanian Bogor
Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Physics Social Sciences

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Perbandingan Klasifikasi SVM dan Decision Tree untuk Pemetaan Mangrove Berbasis Objek Menggunakan Citra Satelit Sentinel-2B di Gili Sulat, Lombok Timur Septiyan Firmansyah; Jonson Lumban Gaol; Setyo Budi Susilo
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 9 No. 3 (2019): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.9.3.746-757

Abstract

Mangrove is one of the most important objects in wetland ecosystems. Mangrove research has been done, one of them is using remote sensing technology. This study aims to assess accuracy of object based image analysis (OBIA) approach on both Support Vector Machine (SVM) and Decision Tree classification methods to classify mangrove and estimate mangrove area in the field study. We selected Kawasan Konservasi Laut Daerah (KKLD) Gili Sulat as a research site. This research used Sentinel-2B satellite imagery. We took field data using stratified random sampling and the amount of the data we collected were 121 points. The classification analysis result with object based showed that SVM had an overall accuracy of 95 % (kappa = 0.86) and Decision Tree classification had an overall accuracy of  93 % (kappa = 0.82). It is caused SVM can reduce the error of classification than Decision Tree. Estimation result based on assessment showed that mangrove using SVM had 634.62 Ha while using Decision Tree had 590.47 Ha
Analisis Penentuan Sebaran Konsentrasi Klorofil-A dan Produktivitas Primer di Perairan Teluk Saleh menggunakan Citra Satelit Landsat OLI 8 Erni Kusumawati; Setyo Budi Susilo; Syamsul Bahri Agus; Arifin Taslim; Yulius Yulius
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 9 No. 3 (2019): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.9.3.671-679

Abstract

Chlorophyll-a is a parameter that can determine the primary productivity in the coastal and ocean. Chlorophyll-a is pigment in phytoplankton that used in photosynthesis. Chlorophyll-a concentration can be detected by ocean color remote sensing by using a mathematical model of satellite image data. The purpose of this research is to modify the algorithm of chlorophyll-a concentration of Landsat OLI 8 Satellite Image data and to show the spatial and temporal distribution of chlorophyll-a concentration. The determination of the algorithm is done using a simple linear regression analysis model between ratio of satellite image band data and value of chlorophyll-a in situ data. The algorithm result is C = 0.416 (green / blue) - 0.183 with R² = 0.785 where C is chlorophyll-a concentration (in mg/m3). Using this algorithm, the spatial distribution of surface concentration of chlorophyll-a can be drawn. Based on analysis of primary productivity that potential of fish resources in the Saleh Bay is 1 327 199.83 ton/years.
Co-Authors . Hendrawan Achmad Fahrudin Achmad Fahrudin Achmad Fahrudin Al Hakim, Muhammad Abdul Ghofur Alimudi, Saiful Amiruddin Tahir Amula Nurfiarini Arifin Taslim Ario Damar Daniel Monintja Devy, Nanda Riska Djadja S . Sjefei Djadja S. Sjafei Dony Apdillah Erni Kusumawati Fredinan Yulianda Heny Suseno Heny Suseno Ilham . Indra Jaya Inul Adkha James Parlindungan Panjaitan Jonson Lumban Gaol Kurniawan, Rika Luky Adrianto M Mukhlis Kamal M. F. Rahardjo M. Mukhlis Kamal Maartianus S. Baroleh Mennofatria Boer Muhammad Rizki Nandika Mulkan Nuzapril Nandika, Muhammad Rizki Paryono - Paryono Paryono Riyadi Subur, Riyadi Rokhmin Dahuri Rokhmin Dahuri Rokhmin Dahuri Rokhmin Dahuri Rokhmin Dahuri S. Wirjoatmodjo Santun R.P. Sitorus Santun R.P. Sitorus Septiyan Firmansyah Sri Suryo Sukoraharjo Syamsul Bahri Agus, Syamsul Bahri Viktor Amrifo Viktor Amrifo Vincentius P Siregar Vincentius Siregar Yoga Candra Ditya Yulia Asyiawati Yulia Asyiawati Yulius Yulius