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HUBUNGAN ANTARA KONSENTRASI KLOROFIL-A DENGAN TINGKAT PRODUKTIVITAS PRIMER MENGGUNAKAN CITRA SATELIT LANDSAT-8 Mulkan Nuzapril; Setyo Budi Susilo; James P. Panjaitan
Jurnal Teknologi Perikanan dan Kelautan Vol 8 No 1 (2017): MEI 2017
Publisher : Fakultas Perikanan dan Ilmu Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3836.056 KB) | DOI: 10.24319/jtpk.8.105-114

Abstract

Chlorophyll-a is a phytoplankton pigment involved in photosynthesis. Chlorophyll-a concentration detection through satellite orbiting can only be infered the concentration of chlorophyll-a at sea surface and could not estimate the sea primary productivity. Sea Primary productivity may last up to a depth of compensation or the depth at which the intensity of light stayed at least 1% of sea surface light intensity. However, the aim of this study is tofind out the relationships between the concentration of chlorophyll-a and primary productivity so that the concentration of chlorophyll-a could be used to predict primary productivity. The linear regression equation have been applied to construct model explaing relationship between the chlorophyll-a concentration and sea primary productivity. The equation explaing on chlorophyll-a concentrations with primary productivity is PP = 22.746 + 95.536Keu (R²) = 0.66 where PP is the sea primary productivity, Keu is the average of chlorophyll-a concentration throughout the water column. The results of these equations can be applied to satellite imagery so that it can assist in monitoring water quality conditions.
DETEKSI PERUBAHAN LUASAN MANGROVE MENGGUNAKAN CITRA LANDSAT BERDASARKAN METODE OBIA DI TELUK VALENTINE PULAU BUANO Saiful Alimudi; Setyo Budi Susilo; James P. Panjaitan
Jurnal Teknologi Perikanan dan Kelautan Vol 8 No 2 (2017): NOVEMBER 2017
Publisher : Fakultas Perikanan dan Ilmu Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (689.558 KB) | DOI: 10.24319/jtpk.8.139-146

Abstract

Kurangnya informasi dan perhatian terhadap kawasan mangrove di Teluk Valentine menjadikan penelitian ini penting dilakukan. Seri Landsat 7 ETM + tahun 2003, dan 2015 digunakan sebagai data perekaman untuk memetakan mangrove dan melihat perubahan di wilayah ini. Penelitian ini bertujuan untuk memetakan perubahan ekosistem mangrove antara tahun 2003 dan 2015, dengan menggunakan citra Landsat berdasarkan metode OBIA dan membandingkan keakuratan metode OBIA dan piksel. Metode analis basis objek atau sering disebut klasifikasi berbasis objek digunakan untuk menganalisis sejauh mana perubahan tutupan mangrove. Hasil penelitian menunjukkan bahwa dengan menggunakan klasifikasi berbasis objek, tutupan hutan bakau sangat baik terdeteksi dengan akurasi 85-88%. Penerapan analisis ini relatif stabil pada periode pengamatan, kawasan ini telah mengalami perubahan dari tahun 2003 ke 2015 sebesar 1.2%, namun perubahan tersebut dimaksudkan penambahan mangrove alami. Perhatian pemerintah daerah diperlukan untuk melestarikan kawasan sebagai kawasan konservasi atau laboratorium alam mengingat kawasannya masih sangat bagus dan tidak dieksploitasi secara berlebihan oleh masyarakat sekitar kawasan Teluk Valentine.
PEMETAAN GEOMORFOLOGI TERUMBU KARANG PULAU TUNDA MENGGUNAKAN KLASIFIKASI BERBASIS OBJEK Fahriansyah Fahriansyah; Jonson Lumban Gaol; James P Panjaitan
Jurnal Teknologi Perikanan dan Kelautan Vol 8 No 2 (2017): NOVEMBER 2017
Publisher : Fakultas Perikanan dan Ilmu Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (957.97 KB) | DOI: 10.24319/jtpk.8.147-156

Abstract

Mapping of coral reefs geomorphic in Tunda Island has not been done before using an object-based image classification. This mapping can be used as the basic of information to planning and area development towards the optimum utilization such as marine ecotourism area. This study aims to mapping coral reef geomorphic zone of Tunda Island using object base classification. Data analysis using multispectral image Worldview-2 with data acquisition of August 25, 2013 and bathymetric profiles. The classification using of multiresolution segmentation. The classification is divided into two levels of classification. Level 1 segmentation using parameter of scale 200, shape 0.6 and compactness 0.4. Level 2 Segmentation using parameter of scale 30, shape 0.6 and compactness 0.4. The classification object segmentation able to produce a map with high accuracy at every level. The classification accuracy of Level 1 is 97% and level 2 is 91%.
ACCURACY IMPROVEMENT ON SEA SURFACE HEIGHT ESTIMATION BASED ON WAVEFORM RETRACKING ANALYSES OF JASON-2 SATELLITE IN JAVA SEA Muhammad R. Hakim; Bisman Nababan; James P. Panjaitan
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 7 No. 2 (2015): Elektronik Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.555 KB) | DOI: 10.29244/jitkt.v7i2.11254

Abstract

A waveform created by the reflected signal from altimeter satellite in offshore is generally in ideal shape (Brown-waveform) and produces an accurate sea surface height (SSH) estimation. However, over coastal waters, the waveform shape becomes complex due to a disruption by reflected signal from land, resulting inaccurate SSH estimation. The objective of this research was to improve the accuracy of SSH estimation employing waveform retracking analyses of Jason-2 altimeter satellite data in the Java Sea during the years of 2012-2014. This study used data from the Sensor Geophysical Data Record type D (SGDR-D) from Jason-2 satellite (cycle 129 - 239) and global geoid undulation data of Earth Gravitational Model 2008 (EGM08). Waveform retracking analyses were conducted using several retracker methods. The performance of the all retrackers were examined using a world reference undulation geoid of EGM08. The results showed that the waveform retracking analyses were able to improve the accuracy of SSH estimation approximately 29.7% in the north coast and 56.4% in the south coast of total non-Brown-waveform in each region. Higher improvement percentage (IMP) of SSH estimation found in the southern coastal areas was due to a relatively smooth coastline formation in this region than in northern coastal region. There was no specific retracker that produce dominant IMP of SSH estimation. However, the  threshold 10% retracker produced better SSH estimation than the other retrackers with dominant IMP values of 57.1% (pass 051), 48.1% (pass 064), and 25.7% (pass 127). OCOG retracker the worst retracker to estimate SSH in the Java Sea.                                                                                                               Keywords: EGM08, waveform retracking, SSH, Jason-2, ocean retracker, threshold retracker
PEMETAAN HABITAT BENTIK BERBASIS OBJEK MENGGUNAKAN CITRA SENTINEL-2 DI PERAIRAN PULAU WANGI-WANGI KABUPATEN WAKATOBI La Ode Khairum Mastu; Bisman Nababan; James P Panjaitan
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 10 No. 2 (2018): Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2017.861 KB) | DOI: 10.29244/jitkt.v10i2.21039

Abstract

Penelitian pemetaan habitat bentik di Pulau Wangi-wangi masih sangat sedikit dilakukan, sehingga ketersediaan data spasial habitat bentik di daerah ini sangat terbatas. Penelitian ini bertujuan untuk memetakan habitat bentik perairan dangkal menggunakan citra Sentinel-2 dengan metode klasifikasi berbasis objek/OBIA dan menghitung tingkat akurasi hasil klasifikasi habitat bentik di perairan Pulau Wangi-wangi Kabupaten Wakatobi. Penelitian ini dilaksanakan di perairan Pulau Wangi-wangi, khususnya perairan Sombu Dive dan sekitarnya. Penelitian ini menggunakan data satelit Sentinel-2 dengan resolusi spasial 10x10 m2 yang diakuisisi pada tanggal 4 April 2017 dan pengambilan data lapangan dilakukan pada bulan Maret - April 2017. Klasifikasi citra dengan metode OBIA menggunakan metode contextual editing pada level 1. Level 2 menggunakan klasifikasi terbimbing dengan beberapa algoritma klasifikasi yaitu support vector machine (SVM), decision tree (DT), Bayesian, dan k-nearest neighbour (KNN) dengan input themathic layer dari data lapangan. Klasifikasi habitat bentik dilakukan pada 12 dan 9 kelas dengan penerapan optimasi skala segmentasi yaitu 1, 1,5, 2, dan 2,5. Berdasarkan metode OBIA, habitat bentik dapat dipetakan dengan tingkat akurasi sebesar 60,4% dan 64,1% pada citra klasifikasi 12 dan 9 kelas secara berturut-turut pada nilai optimum skala segmentasi 2 dengan algoritma SVM.
Pemetaan Kompleksitas Habitat Dasar Perairan Menggunakan Data Batimetri di Perairan Pulau Kemujan Karimunjawa Arip Rahman; Vincentius P. Siregar; James P. Panjaitan
Jurnal Kelautan Tropis Vol 24, No 2 (2021): JURNAL KELAUTAN TROPIS
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jkt.v24i2.10498

Abstract

The complexity of the substrate of the bottom waters describes the diversity of the bottom structure of the waters. The structure of the complexity of bottom waters can be measured by the rugosity. Manual method for measuring rugosity can be used chain method. Besides that rugosity can be calculated using bathymetry data using Surface Area from Elevation Grid Extension tools that integrated in ArcGIS which produces Arc-chord ratio (ACR) rugosity. Based on this method, a flat area has rugosity close to 1, while an area with high elevated will show rugosity value higher then 1 (>1). Measurement of the complexity of the bottom waters is carried out to see the condition of benthic habitat in the shallow waters of Kemujan Island, Karimunjawa Islands. Based on the rugosity index, conditions of bottom waters of the Kemujan Island are quite complex (ACR rugosity index, 2-2.044). The ACR rugosity index correlated quite well with the rugosity index of the field measurement (r = 0.76).  Kompleksitas dasar perairan menggambarkan keragaman struktur dasar perairan. Struktur kompleksitas suatu dasar perairan dapat diukur dengan tingkat kekasaran (rugosity) dasar perairan. Metode pengukuran rugosity secara manual dilakukan dengan menggunakan metode rantai (chain). Selain itu rugosity juga dapat dihitung dengan menggunakan data kedalaman dengan menggunakan Surface Area from Elevation Grid Extension yang terintegrasi pada ArcGIS yang menghasilkan Arc-chord ratio (ACR) rugosity. Berdasarkan metode ini daerah datar memiliki nilai rugosity mendekati 1, sedangkan area dengan relief tinggi akan menunjukkan nilai rugosity yang lebih tinggi (>1). Pengukuran kompleksitas dasar perairan dilakukan untuk melihat kondisi habitat dasar di perairan dangkal Pulau Kemujan Kepulauan Karimunjawa. Berdasarkan indeks rugosity, kondisi dasar perairan Pulau Kemujan memiliki kompleksitas yang cukup tinggi (indeks ACR rugosity 2-2.044). Hal tersebut menggambarkan kondisi dasar perairan di sekitar lokasi penelitian cukup beragam. Indeks rugosity ACR berkorelasi cukup baik dengan indeks rugosity hasil pengukuran lapangan (r=0.76).
Effect of Different Substituted Fish Meal with Maggot Meal for Growth of Jambal Siam (Pangasius hypopthalmus) James Panjaitan; Indra Suharman; Adelina '
Jurnal Online Mahasiswa (JOM) Bidang Perikanan dan Ilmu Kelautan Vol 1, No 2 (2014): Wisuda Oktober Tahun 2014
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Perikanan dan Ilmu Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The research was conducted from March to April 2014 in experimental pond Fishery and Science Faculty of Riau University. The purposed of the research was to knowed the effect of different substituted fish meal with maggot meal that provide the best growth of Jambal siam (Pangasius hypopthalmus). The experiment was designed by Completely Random design with 5 substitution and 3 replication. The result indicated that differnt substitution fish meal with maggot meal doesn’t have significantely effect on growth of Jambal siam (Pangasius hypopthalmus). The best result was achived by treatment E with 100% Maggot meal level. Total absolute body weight, spesific growth rate and feet efficiency was 30,16 grams, 4,76%/ day, and 69,3% respectively, while the best protein retention and survival rate on treatment C ( 50 % of maggot meal) of 44,52 % and 70 % respectively. Water quality during the research are temperature of 29 – 30 0 C, pH of 5 – 6, and disolved oxygen of 4,5 - 5,4 ppm.Key word :Maggot meal, Fish meal,Jambal siam (Pangasius hypopthalmus)
ESTIMASI PRODUKTIVITAS PRIMER PERAIRAN BERDASARKAN KONSENTRASI KLOROFIL-A YANG DIEKSTRAK DARI CITRA SATELIT LANDSAT-8 DI PERAIRAN KEPULAUAN KARIMUN JAWA Mulkan Nuzapril; Setyo Budi Susilo; James Parlindungan Panjaitan
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 Juni 2017
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1018.134 KB) | DOI: 10.30536/j.pjpdcd.2017.v14.a2548

Abstract

Sea primary productivity is an important factor in monitoring the quality of sea waters due to his role in the carbon cycle and the food chain for heterotrophic organisms. Estimation of sea primary productivity may be suspected through the values of chlorophyll-a concentration, but surface chlorophyll-a concentration was only able to explain 30% of the primary productivity of the sea. This research aims to build primary productivity estimation model based on chlorophyll-a concentration value of a surface layer of depth until depth compensation. Primary productivity model of relationships with chlorophyll concentration were extracted from Landsat-8 imagery then it could be used to calculated of sea primary productivity. The determination of the depth classification were done by measuring the attenuation coefficient values using the luxmeter underwater datalogger 2000 and secchi disk. The attenuation coefficient values by the luxmeter underwater, ranges between of 0.13-0.21 m-1 and secchi disk ranged, of 0.12 – 0.21 m-1. The penetration of light that through into the water column where  primary productivity is still in progress or where the depth of compensation ranged from 28.75 – 30.67 m. The simple linier regression model between average value of chlorophyll- concentration in all euphotic zone with sea primary productivity has high correlation, it greater than of surface chlorophyll-a concentration (R2 = 0.65). Model validation of sea primary productivity has high accuracy with the RMSD value of 0.09 and satellite-derived sea primary productivity were not significantly different. The satellite derived of chlorophyll-a could be calculated into sea primary productivity.Abstrak Produktivitas primer perairan merupakan faktor penting dalam pemantauan kualitas perairan laut karena berperan dalam siklus karbon dan rantai makanan bagi organisme heterotrof. Estimasi produktivitas primer perairan dapat diduga melalui nilai konsentrasi klorofil-a, namun konsentrasi klorofil-a permukaan laut hanya mampu menjelaskan 30% produktivitas primer laut. Penelitian ini bertujuan untuk membangun model estimasi produktivitas primer berdasarkan nilai konsentrasi klorofil-a dari lapisan kedalaman permukaan sampai kedalaman kompensasi. Model hubungan produktivitas primer dengan konsentrasi klorofil-a yang diekstrak dari citra satelit Landsat-8 kemudian dapat digunakan untuk mengestimasi produktivitas primer satelit. Penentuan klasifikasi kedalaman dilakukan dengan mengukur nilai koefisien atenuasi menggunakan luxmeter underwater datalogger 2000  dan secchi disk. Nilai koefisien atenuasi dengan menggunakan luxmeter underwater berkisar antara 0,13 -0,21m-1 dan secchi disk berkisar antara 0,12 – 0,21 m-1. Penetrasi cahaya yang masuk ke kolom perairan dimana produksi primer masih berlangsung atau kedalaman kompensasi berkisar antara 28,75 – 30,67 m. Model regresi linier sederhana antara konsentrasi klorofil-a rata-rata seluruh zona eufotik dengan produktivitas primer perairan memiliki korelasi yang lebih tinggi dibandingkan konsentrasi klorofil-a permukaan dengan R2= 0,65. Validasi model produktivitas primer memiliki keakuratan yang tinggi dengan RMSD sebesar 0,09 dan produktivitas primer satelit secara signifikan tidak berbeda nyata dengan produktivitas primer data insitu. Sehingga  nilai konsentrasi klorofil-a satelit dapat ditransformasi menjadi produktivitas primer satelit.
VARIATION AND TREND OF SEA LEVEL DERIVED FROM ALTIMETRY SATELLITE AND TIDE GAUGE IN CILACAP AND BENOA COASTAL AREAS Amelius Andi Mansawan; Jonson Lumban Gaol; James P. Panjaitan
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 1 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (951.14 KB) | DOI: 10.30536/j.ijreses.2016.v13.a2703

Abstract

Observation of sea levels continuously is very important in order to adapt the disasters in the coastal areas. Conventionally observations of sea level using tide gauge, but the number of tide gauge installed along the coast of Indonesia is still limited. Altimetry satellite data is one solution; therefore it is necessary to assess the potential and accuracy of altimetry satellite data to complement the sea level data from tide gauges. The study was conducted in the coastal waters of Cilacap and Bali by analysis data Envisat satellite altimetry for period 2003 to 2010 and data compiled from a variety of satellite altimetry from 2006 to 2014. Data tidal was used as a comparison of altimetry satellite data. The altimetry satellite data in Cilacap and Benoa waters more than 90% could be used to assess the variation and the sea level rise during the period 2003-2010. The rate of sea level rise both the data of tidal and satellite altimetry data indicates the same rate was 3.5 mm/year in Cilacap. in Benoa are 4.7 mm/year and 5.60 mm/year respectively.
Estimasi Kedalaman Perairan Dangkal Menggunakan Citra Satelit Multispektral Sentinel-2A Arip Rahman; Vincentius P. Siregar; James P. Panjaitan
Jurnal Segara Vol 16, No 3 (2020): Desember
Publisher : Pusat Riset Kelautan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (778.761 KB) | DOI: 10.15578/segara.v16i3.8562

Abstract

Estimasi kedalaman perairan dangkal menggunakan data penginderaan jauh menjadi salah satu alternatif pengukuran kedalaman yang terkendala masalah teknis dan logistik. Ekstraksi kedalaman menggunakan citra Sentinel-2A dilakukan di sekitar perairan Pulau Kemujan Taman Nasional Perairan Karimunjawa Jawa Tengah. Sebanyak 2134 data (1280 data training dan 854 data test) hasil pemeruman digunakan pada saat analisis. Dark Object Substraction (DOS) digunakan pada proses awal pengolahan citra Sentinel 2A untuk menghasilkan citra yang terkoreksi atmosferik. Metode algoritma yang digunakan untuk mengestimasi kedalaman antara lain: linear transform, ratio transform dan support vector machine (SVM). Hasil korelasi antara data prediksi kedalaman dan hasil pemeruman tertinggi dihasilkan dari metode algoritma SVM dengan koefisien determinasi (R2)  0,71 (data training) dan 0,56 (data test). Hasil penilaian akurasi menggunakan nilai Root Mean Square Error (RMSE) dan Mean Absolute Error (MAE), metode algoritma SVM memiliki nilai penyimpangan terkecil (< 1 m). Hal tersebut mengindikasikan bahwa metode algoritma SVM memiliki tingkat akurasi yang lebih tinggi dibandingkan dengan kedua metode lainnya.