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Simon I. Patty
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Environmental Science

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Journal : JURNAL ILMIAH PLATAX

 1 
Characteristics of Phosphate, Nitrate and Dissolved Oxygen in Gangga and Siladen Island Waters, North Sulawesi Simon I. Patty
Jurnal Ilmiah PLATAX Vol. 2 No. 2 (2014): EDISI MEI - AGUSTUS 2014
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.2.2.2014.7151

Abstract

Waters of Gangga and Siladen island, North Sulawesi is very important due to their terrestrial-influenced  oceanographic conditions of the Celebes Sea and the Indian Ocean that is rich in marine resources.  Research on the characteristics of the water mass in relation with nutrients, phosphate, nitrate and dissolved oxygen were carried out in the waters Gangga island (May 2011) and Siladen island (July 2011). Phosphate and nitrate levels were analyzed using spectrophotometric method using Nicolet Evolution 100 spectrophotometer, while dissolved oxygen was determined by electrochemical methods. Statistical analysis showed that the nitrate levels in the waters of the Gangga island to the Siladen island is significantly different, while the phosphate and dissolved oxygen levels were not significantly different. The fluctuative concentration of phosphate, nitrate and dissolved oxygen in the Gangga  and Siladen  island waters were influenced by current, the mmovement of water mass, plankton activity and input from the surrounding mainland. Keywords: Phosphate, nitrate, dissolved oxygen, gangga, siladen, north sulawesi. ABSTRAK Perairan pulau Gangga dan pulau Siladen, Sulawesi Utara merupakan perairan yang sangat penting karena kondisi oseanografinya di pengaruhi daratan, Laut Sulawesi dan Samudera Hindia sehingga kaya akan sumber daya laut. Penelitian tentang karakteristik massa air kaitannya dengan zat hara fosfat, nitrat dan oksigen terlarut telah dilakukan di perairan pulau Gangga (Mei 2011) dan pulau Siladen (Juli 2011). Kadar fosfat dan nitrat dianalisa dengan menggunakan metode spektrofotometri dengan menggunakan alat spektrofotometer Nicolet Evolution 100, sedangkan oksigen terlarut ditentukan dengan metoda elektrokimia. Hasil analisis statistik menunjukkan bahwa kadar nitrat di perairan pulau Gangga dengan pulau Siladen adalah berbeda sangat nyata, sedangkan kadar fosfat dan oksigen terlarut tidak berbeda nyata. Tinggi rendahnya kosentrasi fosfat, nitrat dan oksigen terlarut di perairan pulau Gangga dan pulau Siladen dipengaruhi oleh arus, pergerakan massa air, aktifitas plankton dan masukan dari daratan.   Kata kunci: Fosfat, nitrat, oksigen terlarut, Gangga, Siladen, Sulawesi Utara.
Mapping the Condition of Seagrasses Beds in Ternate -Tidore Waters, and Surrounding Areas Simon I. Patty
Jurnal Ilmiah PLATAX Vol. 4 No. 1 (2016): EDISI JANUARI-JUNI 2016
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.4.1.2016.13228

Abstract

Seagrass beds is one of the most prolific shallow water ecosystems, having ecological function in the life of the various marine organisms and other coastal systems. Data and information of seagrass condition in the waters of Ternate, Tidore and surrounding areas are still hardly unexplored. This study aimed to describe the spatial distribution information of seagrass cover percentage, seagrass conditions and environmental characteristics. The basic data used for mapping of seagrass is Landsat 8 on a path 110 row 59 recordings in July 2015. Analysis of overlaying and the interpretation of the seagrass distribution software using "ERMapper, Image Analysis 1.1 on ArcGIS ArcView 3.2 and 10.1". Field test was conducted on frame 50 x 50 cm squares, each square of the recorded species of seagrasses and cover percentage value. Condition assessment based on seagrass cover by (Rahmawati et al., 2014) and (KMLH, 2004). The results show that there are eight species of seagrass found in the waters of the island of Ternate, Tidore and Hiri Maitara island. The highest percentage in the seagrass cover was found in Maitara islands and Hiri Island, i.e ≥ 50%. Seagrass cover conditions in general are relatively "moderate", but the health conditions are less healthy / less wealthy (30 to 59.9%). Keywords: Seagrass beds, seagrass conditions, mapping, satelite image ABSTRAK Padang lamun merupakan salah satu ekosistem perairan dangkal yang paling produktif, mempunyai  fungsi ekologis dalam kehidupan berbagai organisme laut dan sistem pesisir lainnya.  Informasi  data  padang  lamun  di  perairan Ternate, Tidore dan sekitarnya masih belum tereksplorasi dengan baik. Penelitian ini bertujuan  mendeskripsikan  informasi  secara  spasial  sebaran  lamun,  persentase  tutupan, kondisi lamun dan karakteristik lingkungannya. Data dasar yang digunakan untuk pemetaan padang lamun adalah citra Landsat 8 pada path 110 row 59 rekaman Juli  2015. Analisis tumpang susun dan interpretasi sebaran lamun dengan menngunakan perangkat lunak “Ermapper, Image Analysis 1.1 pada ArcView 3.2 dan “ArcGIS 10.1”. Uji lapangan dilakukan pada frame kuadrat 50 x 50 cm, disetiap kuadrat dicatat jenis lamun dan nilai persentase tutupan.  Penilaian kondisi lamun berdasarkan tutupan menurut (Rahmawati dkk., 2014) dan (KMLH, 2004). Hasilnya menunjukkan bahwa  terdapat 8 jenis lamun yang ditemukan di perairan pulau Ternate, pulau Tidore, pulau Hiri dan pulau Maitara. Presentase tutupan lamun tertinggi terdapat di pulau Maitara dan pulau Hiri yaitu ≥ 50 %. Kondisi lamun pada umumnya memiliki tutupan tergolong “sedang”, namun kondisinya kurang sehat/kurang kaya (30-59,9%). Kata kunci: Padang lamun, kondisi lamun, pemetaan, citra satelit   1 Proyek Penelitian RHM-COREMAP, 2015 2 UPT. Loka Konservasi Biota Laut Bitung-LIPI
Dissolved Oxygen in the East Bolaang Mongondow Waters, North Sulawesi Patty, Simon I.; Rizqi, Marenda Pandu; Huwae, Rikardo
Jurnal Ilmiah Platax Vol. 10 No. 1 (2022): ISSUE JANUARY-JUNE 2022
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.v10i1.40434

Abstract

Oxygen in seawater comes from the air through diffusion and photosynthesis. This study aims to determine the dissolved oxygen content, NAEC (Normal Atmospheric Equilibrium Concentration), and AOU (Apparent Oxygen Utilization) in East Bolaang Mongondow waters. The analysis showed that the dissolved oxygen content in the surface layer ranged from 6.01-7.05 mg/l; 5.91-6.98 mg/l (5 m depth); and 5.75-6.90 mg/l (near bottom depth). NAEC is closely related to water temperature and implicitly increases with depth. The highest NAEC value of 5.90 mg/l (t=28.0ºC) was found at the bottom depth, and the lowest NAEC of 5.63 mg/l (t=30.0ºC) was found at the surface layer. The dissolved oxygen saturation level of more than 100% and the average positive AOU value at 0.59-0.81 mg/l describe the amount of oxygen available in the surface layer.Keywords: Dissolved Oxygen; Normal Atmospheric Equilibrium Concentration (NAEC); Apparent Oxygen Utilization (AOU); East Bolaang Mongondow.AbstrakOksigen dalam air laut bersumber dari udara melalui proses difusi dan hasil fotosintesis. Penelitian ini bertujuan untuk mengetahui kandungan oksigen terlarut, NAEC (normal atmospheric equilibrium concentration) dan AOU (apparent oxygen utilization) di perairan Bolaang Mongondow Timur. Hasil analisis menunjukkan bahwa kandungan oksigen terlarut di lapisan permukaan berkisar antara 6,01-7,05 mg/l; kedalaman 5 meter 5,91-6,98 mg/l dan dekat dasar 5,75-6,90 mg/l. NAEC sangat berhubungan dengan suhu air dan secara implisit konsentrasinya akan semakin tinggi dengan bertambahnya kedalaman. Nilai NAEC tertinggi 5,90 mg/l (t=28,0ºC) ditemukan pada kedalaman dekat dasar dan  NAEC terendah 5,63 mg/l (t=30,0ºC) ditemukan pada lapisan permukaan. Tingkat kejenuhan oksigen terlarut >100 % dan rata-rata nilai AOU positif (0.59-0.81 mg/l) menggambarkan banyaknya kandungan oksigen yang tersedia pada lapisan permukaan.Kata kunci: oksigen terlarut; normal atmospheric equilibrium concentration (NAEC); apparent oxygen utilization (AOU); Bolaang Mongondow Timur.
Analysis of Mangrove Vegetation and Distribution Using Landsat 8 Images In Bolaang Mongondow East, North Sulawesi Patty, Simon I.; Nurdiansah, Doni; Rizqi, Marenda Pandu; Huwae, Rikardo
Jurnal Ilmiah Platax Vol. 10 No. 2 (2022): ISSUE JULY-DECEMBER 2022
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.v10i2.41069

Abstract

Mangrove is one of the objects that can be identified by remote sensing technology using satellite imagery. Analysis of the distribution and density of mangrove vegetation using Landsat 8 imagery was carried out in Bolaang Mongondow Timur, North Sulawesi in September 2020. This study aims to map the distribution of mangroves and determine the correlation between NDVI values, canopy cover, and mangrove density. The data analysis used Landsat 8 images with ENVI 5.3 and ArcGIS 10.1 software. Maximum likelihood classification is used to separate mangrove and non-mangrove features. The calculation of mangrove vegetation density using the NDVI algorithm and single-channel classification using the density slice method to divide mangrove density based on the range of pixel values of the NDVI image. Next, to test the accuracy of the classification results using an error matrix (confusion matrix) and the NDVI vegetation index correlation test compared with canopy cover and density data. The classification resulted in four different land cover classes with an overall accuracy of 97.70% and a kappa coefficient of 0.9688. The mangrove vegetation distribution from the classification results is 524.75 ha. The NDVI correlation with the percentage of canopy cover is very significant with a correlation coefficient (r) = 0.9516, while the NDVI correlation with density resulted in moderate correlation (r = 0.5315).Keywords: density; mangrove; Landsat 8; NDVI                                             AbstrakMangrove merupakan salah satu objek yang dapat diidentifikasi menggunakan teknologi penginderaan jauh yakni memanfaatkan citra satelit. Analisis sebaran dan kerapatan vegetasi mangrove menggunakan citra Landsat 8 telah dilakukan di Bolaang Mongondow Timur, Sulawesi Utara pada bulan September 2020. Penelitian ini bertujuan untuk memetakan sebaran mangrove dan mengetahui hubungan korelasi antara nilai NDVI dengan tutupan kanopi dan kerapatan mangrove. Pengolahan data citra Landsat 8 dengan perangkat lunak ENVI 5.3 dan ArcGIS 10.1. Klasifikasi maximum likelihood digunakan untuk memisahkan fitur mangrove dan non mangrove. Perhitungan kerapatan vegetasi mangrove dengan algoritma NDVI dan klasifikasi saluran tunggal menggunakan metode density slice untuk membagi kerapatan mangrove berdasarkan rentang nilai piksel citra NDVI. Uji akurasi hasil klasifikasi menggunakan matriks kesalahan (confussion matriks) dan uji korelasi indeks vegetasi NDVI dengan data tutupan kanopi dan kerapatan. Hasil klasifikasi mendapatkan empat kelas tutupan lahan yang berbeda dengan overall akurasi sebesar 97,70 % dengan kappa coefisien sebesar 0,9688. Luas sebaran vegetasi mangrove dari hasil klasifikasi adalah 524,75 ha. Korelasi NDVI  dengan persentase tutupan kanopi termasuk korelasi sangat kuat dengan koefisien korelasi r = 0,9516 sedangkan korelasi NDVI  dengan kerapatan termasuk korelasi sedang (r = 0,5315).Kata kunci: kerapatan; mangrove; Landsat 8; NDVI 
Temperature, Salinity and Dissolved Oxygen West and East seasons in the waters of Amurang Bay, North Sulawesi Patty, Simon I.; Huwae, Rikardo
Jurnal Ilmiah Platax Vol. 11 No. 1 (2023): ISSUE JANUARY-JUNE 2023
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.v11i1.46651

Abstract

Observations of temperature, salinity, and dissolved oxygen have been carried out in Amurang Bay waters, North Sulawesi. This study aims to determine the temperature, salinity, and dissolved oxygen during the west and east seasonal monsoons. The statistical analysis results using the t-test showed that the temperature, salinity, and dissolved oxygen in the West monsoon with the east monsoon were significantly different. Temperature, salinity, and dissolved oxygen in the west monsoon are lower than in the east. Variations in temperature, salinity, and dissolved oxygen are influenced by atmospheric conditions, weather, rainfall, and current patterns. Implicitly, temperature and salinity can affect the solubility of oxygen in the East monsoon. The value of AOU (Apparent Oxygen Utilization) in the west monsoon is less than 0.00 mg/l (negative), which indicates that oxygen is very much needed for the process of respiration and decomposition of organic substances during the west monsoon. Keywords: oceanographic conditions, temperature, salinity, dissolved oxygen, Amurang Bay.
Mapping Benthic Habitat Distribution and Coral Reef Health Index in Ternate Island and Tidore Island, North Maluku Patty, Simon I.; Souhoka, Jemmy; Makatipu, Petrus C.; Rizqi, Marenda Pandu
Jurnal Ilmiah Platax Vol. 12 No. 1 (2024): ISSUE JANUARY-JUNE 2024
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.v12i1.54054

Abstract

Coral reefs are underwater marine organisms whose coverage can be identified using remote sensing technology utilizing satellite imagery. The benthic habitats classification and coral reef health index analysis were carried out on the Ternate and Tidore islands in June 2021. This study aims to map the distribution of benthic habitat as well as calculate the value of the coral reef health index. The processing of satellite imagery data from Landsat 8, using ENVI 5.3 and ArcGIS 10.1 software. The "depth invariant index" algorithm is used in the image sharpening process (Lyzenga, 1981). The maximum likelihood classification technique is used to identify substrate type, with a confusion matrix used to test its accuracy. The coral reef health index assessment is based on the condition of live coral cover, resilience level, and reef fish biomass. The results from water column image classification showed that there were four classes of habitat, i.e. coral, seagrass, sand, and rubble with an overall accuracy value of 85.86% and kappa coefficient of 0.80605. The total area of classified coral reefs is 1152.85 hectares. The coral reef health index values ranged from 2 to 8 with an average of 5, which translates to a moderate percentage of live coral cover, high resilience, and low fish biomass. Keywords: coral reefs, benthic habitat, health index, Landsat 8 images.   Abstrak Terumbu karang merupakan objek tutupan bawah air laut yang dapat diidentifikasi menggunakan teknologi penginderaan jauh yakni memanfaatkan citra satelit. Klasifikasi habitat bentik dan analisis indeks kesehatan terumbu karang telah dilakukan di pulau Ternate dan pulau Tidore pada bulan Juni 2021. Penelitian ini bertujuan untuk memetakan sebaran habitat bentik serta mengetahui nilai indeks kesehatan terumbu karang. Pengolahan data citra Landsat 8 dengan perangkat lunak ENVI 5.3 dan ArcGIS 10.1. Proses penajaman citra menggunakan algoritma “depth invariant index” (Lyzenga, 1981). Teknik klasifikasi maximum likelihood digunakan untuk identifikasi objek dasar perairan dan uji akurasi menggunakan confusion matrix. Penilaian indeks kesehatan terumbu karang berdasarkan kondisi tutupan karang hidup, tingkat resiliensi dan biomassa ikan karang. Hasil klasifikasi citra kolom air mendapatkan empat kelas habitat yaitu karang, lamun, pasir dan pecahan karang mati (rubble) dengan nilai akurasi keseluruhan sebesar 85,86 % dan koefisien kappa sebesar 0,80605. Total luasan area terumbu karang hasil klasifikasi adalah 1152,85 ha. Nilai indeks kesehatan terumbu karang berkisar antara 2 sampai 8, dengan rata-rata 5 yang menggambarkan persentase tutupan karang hidup sedang, tingkat resiliensi tinggi dan biomassa ikan rendah. Kata kunci: terumbu karang, habitat bentik, indeks kesehatan, citra Landsat 8.
Analysis of Mangrove Vegetation Index Using Landsat 8 Images in Dodinga Bay, West Halmahera Patty, Simon I.; Nurdiansah, Doni; Rizqi, Marenda Pandu; Akbar, Nebuchadnezzar; Huwae, Rikardo
Jurnal Ilmiah Platax Vol. 13 No. 1 (2025): ISSUE JANUARY-JUNE 2025
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35800/jip.v13i1.60830

Abstract

Mangrove vegetation can be easily recognized from remote-sensing satellite images compared to other terrestrial vegetation. The vegetation index is applied to the satellite images to highlight the aspect of vegetation density. This study aims to determine the correlation between the value of the vegetation index and mangrove canopy cover data to achieve a proper vegetation index to estimate the density of the mangrove canopy. The data needed are satellite imagery from Landsat 8 and mangrove canopy cover in sampling locations along the coast of Dodinga Bay, West Halmahera. Image data analysis includes radiometric correction, image sharpening, masking, classification, and accuracy tests. The vegetation index algorithms used were NDVI, GNDVI, and IM, and regression analysis was carried out for correlation tests. The analysis results obtained four different land cover classes with an overall accuracy of 97.70% and a kappa coefficient of 0.9688. The IM vegetation index showed an excellent correlation with mangrove canopy cover compared to GNDVI and NDVI. The determination coefficient (R²) of the IM is 0.6765; GNDVI (0.4897) and NDVI (0.4825). The IM classification produces four levels of mangrove canopy density, i.e., sparse (7.40 ha), moderate (628.33 ha), dense (921.22 ha), and very dense (16.45 ha). Keywords: mangrove, Landsat 8 images, vegetation index, Dodinga Bay Abstrak Objek vegetasi mangrove paling mudah diidentifikasi dengan menggunakan citra satelit penginderaan jauh dibandingkan objek vegetasi darat lainnya. Indeks vegetasi diterapkan terhadap citra untuk menonjolkan aspek kerapatan vegetasi. Penelitian ini bertujuan mengetahui korelasi antara nilai indeks vegetasi dengan data tutupan kanopi mangrove, sehingga didapatkan indeks vegetasi yang sesuai untuk menduga kerapatan kanopi mangrove. Data yang diperlukan yaitu citra Landsat 8 dan tutupan kanopi mangrove di lapangan. Analisis data citra terdiri dari koreksi radiometrik, penajaman citra, masking, klasifikasi dan uji akurasi. Algoritma indeks vegetasi yang digunakan yaitu NDVI, GNDVI dan IM, serta dilakukan analisis regresi untuk uji korelasi. Hasil analisis mendapatkan empat kelas tutupan lahan yang berbeda dengan overall akurasi sebesar 97,70 % dan kappa coefisien sebesar 0,9688. Indeks vegetasi IM menunjukkan korelasi sangat baik dengan tutupan kanopi mangrove dibandingkan GNDVI dan NDVI. Koefisien determinasi (R²) IM adalah 0,6765; GNDVI (0,4897) dan NDVI (0,4825). Klasifikasi IM menghasilkan empat tingkat kerapatan kanopi mangrove yaitu mangrove jarang (7,40 ha), mangrove sedang (628,33 ha), mangrove lebat (921,22 ha), dan mangrove sangat lebat (16,45 ha). Kata kunci: mangrove, citra Landsat 8, indeks vegetasi, Teluk Dodinga
Co-Authors Huwae, Rikardo Jemmy Souhoka Makatipu, Petrus C. Nebuchadnezzar Akbar Nurdiansah, Doni Rizqi, Marenda Pandu