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All Journal Buletin PSP Jurnal Teknologi Perikanan dan Kelautan Jurnal Ilmu dan Teknologi Kelautan Tropis Indonesian Journal of Electronics and Instrumentation Systems Maspari Journal ILMU KELAUTAN: Indonesian Journal of Marine Sciences Waste Technology Maspari Journal Jurnal Ilmu Kelautan Spermonde Jurnal Kelautan Tropis Aceh Journal of Animal Science Jurnal Teknologi dan Sistem Komputer Journal of Applied Geospatial Information Omni-Akuatika JURNAL ILMIAH GEOMATIKA JURNAL INTEGRASI Jurnal Penelitian Perikanan Indonesia Jurnal Kelautan Nasional Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital PELAGICUS: Jurnal IPTEK Terapan Perikanan dan Kelautan Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital SNTE
Hestirianoto, Totok
Departemen Ilmu Dan Teknologi Kelautan, Fakultas Perikanan Dan Ilmu Kelautan, Institut Pertanian Bogor, Jalan Agatis, Kampus IPB Dramaga, Bogor 16680, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Library & Information Science Mathematics Mechanical Engineering Physics Other

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PENGUKURAN NILAI TARGET STRENGTH ANAKAN IKAN GABUS (Channa striata) KONDISI TERKONTROL DENGAN SIMRAD EK-15 ECHOSOUNDER Siahaan, Gracia Tiffany; Pujiyati, Sri; Hestirianoto, Totok; Solikin, Steven
Jurnal Teknologi Perikanan dan Kelautan Vol 15 No 3 (2024): OKTOBER 2024
Publisher : Fakultas Perikanan dan Ilmu Kelautan, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24319/jtpk.15.235-244

Abstract

Ikan gabus (Channa striata) merupakan ikan karnivora yang banyak ditangkap karena rasa dagingnya yang gurih. Keberadaan ikan gabus di Indonesia menyebar dengan sangat luas, namun ancaman terhadap anakan gabus secara terus menerus dapat berakhir dengan kepunahan. Hal ini menjadi penting untuk menganalisis hubungan antara Target Strength (TS) dengan panjang total anakan ikan Gabus (Channa striata), dengan menggunakan instrumen echosounder SIMRAD EK15 untuk manajemen sumber daya, serta mengevaluasi kesehatan populasi ikan gabus. Penelitian dilakukan menggunakan 15 ekor ikan gabus dengan rentang panjang badan ikan 10-15 cm, memiliki rentang nilai TS rata-rata -46,80 dB sampai -45,01 dB. Hubungan antara panjang total ikan gabus dan nilai target strength mempunyai hubungan yang kuat dengan nilai koefisien korelasi sebesar 0,8531 dan koefisien determinasi (R2) sebesar 0,7279, dengan persamaan TS= 64,439ln(L) -215,66.
Acoustic Sediment Classification Using High-Frequency (400 kHz) Multibeam Data in Pari Water of Seribu Island, Indonesia Handoko, Dadang; Manik, Henry Munandar; Hestirianoto, Totok; Priandana, Karlisa; Hasan, Rozaimi Che
ILMU KELAUTAN: Indonesian Journal of Marine Sciences Vol 30, No 1 (2025): Ilmu Kelautan
Publisher : Marine Science Department Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ik.ijms.30.1.135-144

Abstract

Seafloor classification is essential for understanding sediment distribution, marine habitat characteristics, and resource management. Therefore, this study aimed to classify seafloor sediment in the Pari water, Indonesia using high-frequency (400 kHz) backscatter data obtained through the Multibeam Echosounder T-50P. The Angular Range Analysis (ARA) method was applied to analyze backscatter intensity variations across different incidence angles, to enhance the accuracy of sediment classification in this shallow marine environment. Data acquisition was collected using the T-50P, which captured high-resolution acoustic signals from varying angles to generate angular response curves. Analysis was conducted in the curves were then analyzed to differentiate sediment types, with ground-truth sediment samples collected to validate classification outcomes. The result showed that backscatter intensity mosaic had an intensity range of -27 dB to -37.5 dB. Applying ARA enabled the identification of 12 sediment classes, including sandy silt, coarse silt, and clayey sand. Sediment distribution maps, generated via FMGT and visualized with ArcGIS, indicated a predominance of fine-grained sediments. The FMGT-based classification tended to prioritize finer sediment categories, likely due to the acoustic limitations in detecting granular details. Conversely, the in-situ analysis of 15 sediment samples revealed medium sand as the predominant sediment type, accompanied by smaller proportions of coarse sand and coral fragments. The discrepancies between the in-situ sampling and FMGT results were primarily due to the operational frequency of the MBES system, which limits the acoustic signal's penetration to the surface of the seabed. This highlights the importance of in-situ sampling to complement acoustic data, especially in accurately seabed characterization. 
Klasifikasi Gelembung Gas Menggunakan Multibeam Echosounder dan Machine Learning Rabbani, Mochamad Rafif; Manik, Henry Munandar; Hestirianoto, Totok
Jurnal Kelautan Tropis Vol 28, No 2 (2025): JURNAL KELAUTAN TROPIS
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jkt.v28i2.26778

Abstract

The urgency of detecting gas bubbles in the water column is crucial in various fields, ranging from environmental monitoring to detecting underwater gas leaks. One method that can be used to detect gas bubbles is the Multibeam Echosounder. However, processing Multibeam Echosounder data is prone to human error and inefficient in terms of time, necessitating a more practical approach, such as utilizing Artificial Intelligence, specifically Machine Learning. This study aims to classify gas bubbles using Multibeam Echosounder and Machine Learning and determine the best algorithm. The acquired acoustic data were first processed using FMMidwater Fledermaus software for feature extraction and depth analysis in the water column, followed by target tagging on the echogram as a visual labeling process for Machine Learning model input. Three algorithms were tested: Random Forest, K-Nearest Neighbor, and Support Vector Machine. Model evaluation was conducted using a confusion matrix to generate accuracy, F1-score, and kappa coefficient values. The evaluation results showed that the Random Forest algorithm achieved the highest accuracy of 89.02%, followed by Support Vector Machine with 86.76% and K-Nearest Neighbor with 85.41%. These findings demonstrate that the Machine Learning approach effectively classifies gas bubbles in the water column and distinguishes them from other objects in the water column.   Kepentingan pendeteksian gelembung gas di kolom air menjadi urgensi dalam berbagai bidang, misalnya dalam pemantauan lingkungan hingga deteksi kebocoran gas bawah laut. Salah satu metode yang dapat digunakan dalam mendeteksi gelembung gas adalah dengan menggunakan Multibeam Echosounder. Namun, pengolahan data Multibeam Echosounder rawan terjadi human error dan tidak cukup efisien dalam skala waktu, sehingga diperlukan metode praktis dalam pengolahan data Multibeam, salah satunya adalah dengan menggunakan bantuan Artificial Intelligence, yaitu Machine Learning. Penelitian ini bertujuan untuk mengklasifikasikan gelembung gas dengan menggunakan Multibeam Echosounder dan Machine Learning, serta menentukan algoritma terbaik. Data akustik yang telah diakusisi diolah terlebih dahulu dengan bantuan perangkat lunak FMMidwater Fledermaus untuk ekstraksi fitur dan kedalaman objek di kolom air, serta proses tagging target pada echogram sebagai proses pelabelan secara visual untuk input pada model Machine Learning. Terdapat tiga algoritma yang diuji, yaitu Random Forest, K-Nearest Neighbor dan Support Vector Machine. Evaluasi model menggunakan confusion matrix untuk menghasilkan nilai akurasi, F1-Score dan koefisien kappa. Evaluasi performa model menunjukkan algoritma Random Forest memiliki nilai akurasi tertinggi yaitu 89.02 % diikuti oleh Support Vector Machine dengan akurasi 86.76% dan K-Nearest Neighbor dengan akurasi 85.41%. Hasil ini membuktikan bahwa pendekatan Machine Learning mampu mengklasifikasikan gelembung gas di kolom air serta dapat membedakannya terhadap objek lain di kolom air
Prototype Testing of Automatic Vessel Tracking System using Web-Based Visualization Nazzla, Rauzatul; Hestirianoto, Totok; Pujiyati, Sri
PELAGICUS Volume 3 Nomor 2 Tahun 2022
Publisher : Politeknik Kelautan dan Perikanan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/plgc.v3i2.10609

Abstract

Automatic Tracking System is an example in the development of navigation technology that is needed in every means of transportation by land, water, or air. An example of its application in the field of fisheries management is the Vessel Monitoring System (VMS). The purpose of this study was to develop a telemetry technique particularly automatic vessel tracking system. In this study is expected to produce a prototype which can provide information about the movement of traditional fishing boats, especially in coastal areas. Prototype testing in this study was limited to the performance of a prototype based on the capability of the electronics and the resulting output data. Output data obtained by two methods: (1) the trial was stationary, and (2) mobile test. This study also examined the comparison between tracker prototype with GPS handheld. Mobile tracker marks the position automatically whenever the tool is turned on. The increasing distance between the transmitter unit to the receiver unit, the deviation would be even greater. This tool was sensitive in responding and quickly perform the recording every movement. When compared to handheld GPS, this tool has good accuracy and precision indicated by a 95% confidence interval.
PERBANDINGAN ANTARA MARINE ACOUSTIC REMOTE SENSING DAN SWEPT AREA TRAWL DALAM PENDUGAAN DENSITAS IKAN DEMERSAL DI PERAIRAN TARAKAN Simbolon, Domu; Priatna, Asep; Hestirianoto, Totok; Purbayanto, Ari
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 2 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i2.3312

Abstract

The use of hydroacoustic surveys simultaneously with trawl swept area is expected to complement and increase the accuracy each other in estimation of the fish stock resources, especially demersal fish. Therefore, advantages and disadvantages of each method will be disclosed. The purpose of this study was to compare the density of demersal fish from detection of hydroacoustic surveys toward catches of bottom trawl, and to determine the factors that influence differences in fish density estimated of swept area and acoustic method. The study was conducted on May, August and November 2012 around Tarakan waters, North Borneo, using echo sounder Simrad EY60-120 kHz and bottom trawl simultaneously to measure density of demersal fish. Demersal fish density estimation of the two methods showed a highly significant difference. Difference in the estimation of fish density was affected by catchability, dead zone area of trawling, and fish behavior.
EFEKTIVITAS ATRAKTOR CUMI-CUMI DI LOMBOK TIMUR, NUSA TENGGARA BARAT Mulyono, Mulyono; Imron, Mohammad; Hestirianoto, Totok; Kholilullah, Ibrahim; Prasetiyo, Shidiq Lanang; Komarudin, Didin; Yuwandana, Dwi Putra
Jurnal Teknologi Perikanan dan Kelautan Vol 14 No 1 (2023): MEI 2023
Publisher : Fakultas Perikanan dan Ilmu Kelautan, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3240.318 KB) | DOI: 10.24319/jtpk.14.55-64

Abstract

Salah satu teknologi yang dapat mendukung peningkatan populasi cumi-cumi di alam adalah teknologi atraktor cumi-cumi. Atraktor cumi-cumi dapat berfungsi sebagai suatu ekosistem baru dan dapat mengumpulkan cumi-cumi. Tujuan penelitian ini adalah menentukan karakteristik perairan tempat pemasangan atraktor cumi-cumi, menentukan desain kontruksi atraktor cumi-cumi, dan menentukan efektivitas pemasangan atraktor terhadap hasil tangkapan cumi-cumi. Metode penelitian berupa eksperimental fishing dan studi literatur digunakan dalam penelitian ini. Hasil penelitian menunjukkan suhu permukaan laut di periaran Labuhan Haji dan Tajung Luar secara berurutan berkisar 27,10-28,29°C dan 28,15-28,79°C, kondisi dasar perairan Labuhan Haji pasir berlumpur dan Tanjung Luar pasir berbatu. Desain atraktor berbentuk tabung dengan diameter 60 cm, panjang 120 cm, dan berwarna hitam. Pemasangan atraktor efektif mengumpulkan cumi-cumi.
DISTRIBUTION OF PELAGIC FISH IN SOUTH CHINA SEA USING GEOSTATISTICAL APPROACH Hidayat, Esa Fajar; Pujiyati, Sri; Suman, Ali; Hestirianoto, Totok
Jurnal Ilmu Kelautan SPERMONDE VOLUME 4 NUMBER 1, 2018
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jiks.v4i1.3800

Abstract

Pelagic fish are spesies that live in water column at depth of 100 to 200 meters from surface. They migrate as a group looking for nutrient and spawning place. Potential fisheries comodities in Indonesia including pelagic fish have high economic value. Then, stock assessment of pelagic fish measurement is important to researched. The research was conducted in May – June 2016 surrounding South China Sea waters using Madidihang 02 Research Vessel operated by Marine Fisheries Affair (MFA) Republic of Indonesia. To estimate the density of pelagic fish hydro-accoustic equipment and oceanography parameters were used and measured during the campaign. The split beam echosounder was use in aim to obtain precission position and number of fish target. The highest density of fish was found around Tambelan Island and Anambas Island. Statistically pelagic fish density has correlation with chlorophyll-a, salinity, temperature, and sea current velocity. The statistical analysis between pelagic fish density and those oceanography parameters (as statistic variables) yields positive vector correlation.
KUANTIFIKASI HAMBUR BALIK AKUSTIK DASAR LAUT MENGGUNAKAN SCIENTIFIC SINGLE BEAM ECHOSOUNDER Manik, Henry Munandar; Totok Hestirianoto; Sri Pujiyati; Elson, La
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 14 No. 1 (2022): 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 | DOI: 10.29244/jitkt.v14i1.37184

Abstract

Teknologi hidroakustik mampu melakukan kuantifikasi terhadap substrat dasar laut dan dapat memperkirakan secara akurat dan mendekati real time terhadap karakter akustik yang dimiliki oleh masing-masing jenis substrat. Tujuan dari penelitian ini adalah melakukan kuantifikasi hambur balik akustik dasar laut dalam upaya pengembangan teknologi informasi kelautan. Akusisi data menggunakan instrumen akustik Single Beam Echosounder Simrad EK-15 pada frekuensi 200 kHz. Pengolahan dan analisis data meliputi hambur balik akustik, tipe sedimen, komputasi acoustics bottom backscattering substrat dasar laut dan analisis spasial acoustic backscattering dasar laut di perairan Pulau Lancang. Hasil penelitian ini menunjukkan bahwa nilai hambur balik akustik substrat dasar laut berdasarkan nilai SS dan ukuran partikel di setiap stasiun sampling yaitu tipe substrat pasir -21,08 dB sampai -24,55 dB, pasir halus -25,67 dB sampai -26,67 dB, dan pasir halus sekali berkisar antara -27,42 dB sampai -28,03 dB. Berdasarkan rentang nilai hambur balik akustik yang didapatkan dari stasiun sampling diperoleh klasifikasi jenis substrat dasar laut di sepanjang lajur survei yaitu pasir kasar sekali, pasir kasar, pasir sedang, pasir halus, pasir halus sekali, lanau kasar, lanau sedang, lanau halus, lempung kasar dan lempung halus pada rentang nilai -47,85 dB sampai -17,07 dB. Substrat pasir paling banyak ditemukan di lokasi penelitian dengan komposisi yang lebih besar dibandingkan dengan lanau dan lempung. Nilai hambur balik akustik sangat dipengaruhi oleh ukuran partikel, bentuk morfologi dan relief dasar laut.
Rancang Bangun Sistem Monitoring Kelembaban dan Suhu Pasir Sarang Penyu Berbasis Internet of Things (IoT) Santoso, Hendi; Hestirianoto, Totok; Jaya, Indra; Pujiyati, Sri
Seminar Nasional Teknik Elektro Vol. 3 No. 1 (2023): SNTE II
Publisher : Forum Pendidikan Tinggi Teknik Elektro Indonesia Pusat

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

Abstract

Penyu merupakan jenis reptilia laut yang hidup di daerah tropis dan subtropis. Penyu merupakan hewan yang mempunyai sifat Temperature-dependent Sex Determination (TSD). Suhu saat masa inkubasi telur menentukan jenis kelamin betina atau jantan. Penyu yang merupakan hewan berdarah dingin tidak bisa mengerami telurnya sendiri. Keberhasilan penetasan telur penyu secara alamiah dipengaruhi oleh kondisi lingkungan seperti: faktor letak sarang, kedalaman sarang, suhu sarang, kelembapan sarang dan lingkungan sekitarnya. Sistem monitoring yang dikembangkan oleh penelitian ini yaitu sistem monitoring secara real time dan berbasis IoT menggunakan mikrokontroler Arduino Uno dan NodeMcu 6288. Penelitian ini bertujuan untuk memberikan kemudahan bagi peneliti atau masyarakat dalam pengukuran kelembapan dan suhu pasir yang dimanfaatkan untuk bidang-bidang tertentu. Pengukuran suhu pasir menggunakan sensor DS18B20 waterproof, kelembapan pasir menggunakan sensor SKU SEN:0193 serta suhu dan kelembapan udara menggunakan DHT22. Modul sdcard berfungsi untuk menyimpan data hasil perhitungan sensor secara realtime dan terus-menerus. Desain alat ukur dirancang untuk mudah dibawa (portable) dan mudah untuk digunakan. Bahan yang digunakan adalah plastik poly propylene yang mempunyai dimensi 11x8x18 cm. Instrumen ini dapat mencatat secara autonomous dan logger setiap 5 menit sekali dan di tampilkan ke web server dan aplikasi smartphone. Alat ini mampu memberikan informasi data suhu pasir, kelembapan pasir, suhu udara dan kelembapan udara pada sarang penyu semi alami. Berdasarkan hasil pengukuran menggunakan instrumen, suhu pasir sarang penyu semi alami Konservasi Penyu Pangumbahan berkisar antara 27,9 ℃ – 33,2 ℃ dengan rata-rata 30,2℃. Suhu udara berkisar antara 21,5 ℃ – 38,9 ℃ dengan rata-rata 27,5 ℃. Kelembapan pasir berkisar antara 21% – 41% dengan rata-rata 34,3%. Kelembapan udara 38,1% – 89,7% dengan rata-rata 81,9%.
Echogram Image Analysis for Pelagic Fish School Classification in Bungus Waters, West Sumatra Lansky, Jovian; Solikin, Steven; Pujiyati, Sri; Hestirianoto, Totok
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 17 No. 3 (2025): 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 | DOI: 10.29244/jitkt.17.3.69567

Abstract

Tropical marine fisheries are characterized by high species diversity but low individual abundance per species within the same water column, making the detection of distinct fish schools challenging using hydroacoustic technology. However, a hydroacoustic survey conducted in Bungus, West Sumatra, in October 2023 revealed the presence of approximately 14 identifiable fish schools of varying sizes, indicating the potential for further analytical investigation. This study aims to characterize and classify fish schools by analyzing echogram imagery and extracting key acoustic parameters through a statistical multivariate approach. Acoustic data were collected using a Simrad EK-15 echosounder operating at 200 kHz. Subsequent data processing was performed in Echoview, followed by multivariate analysis. From an initial dataset of 24 detected schools, 12 parameters were retained for analysis. These parameters were categorized into three groups: (1) energetic parameters, including target strength (TS), volume backscattering strength (Sv), area backscattering strength (Sa), skewness, and kurtosis; (2) morphometric parameters, consisting of school height, length, perimeter, and volume; and (3) bathymetric parameters, represented by average school depth. Latitude and longitude were included as supplementary spatial descriptors. Among the 12 parameters, latitude did not contribute to school characterization and was therefore excluded from further analysis. Multivariate results indicated that morphometric parameters (particularly school height and area) and energetic parameters (Sa and TS) were the most influential in differentiating school structure. Cluster analysis based on the remaining 11 parameters identified two distinct groups of fish schools: Group 1, comprising 14 schools (58.3%), and Group 2, comprising 10 schools (41.7%). These findings demonstrate that integrating hydroacoustic metrics with multivariate statistical methods provides an effective framework for identifying and characterizing fish schools in tropical waters with inherently complex species assemblages.
Co-Authors Acta Withamana Adi Lutfi Hanafi Agustina Sartika Yos Ekaristi Manik Aisyah Aisyah Ali Suman Alianto , Amron Amron Andi Achmadi Ari Purbayanto Asep Ma'mun Asep Priatna Asep Priatna Augy Syahailatua Ayi Rahmat Baigo Hamuna Baigo Hamuna Chikarista Irfangi DEDI JUSADI Domey Moniharapon Domu Simbolon Dony Apdillah Dwi P. I. Mahdi Dwi Putra Yuwandana Elson, La Freddy Supriyadi Freddy Supriyadi Handoko, Dadang Hasan, Rozaimi Che Hendi Santoso Henry Munandar Manik Hidayat, Esa Fajar Imam Mudita Indra Jaya Indra Jaya Indra Jaya Indra Jaya Indra Jaya Indra Jaya Indra Jaya Jonson Lumban Gaol Karen von Juterzenka Karlisa Priandana Keni Sultan Kholilullah, Ibrahim Krisna Rendi Awalludin Lansky, Jovian Lestari, Nurhaliza Amalia Mohammad Imron Muhamad Rakif Panguale Muhamad Zainuddin Lubis Muhammad Banda Selamat Muhammad Banda Selamat Muhammad Farhan Muhammad Mujahid Muhammad Z. Lubis Mujizat Kawaroe Mulyono Mulyono Nazzla, Rauzatul Prasetiyo, Shidiq Lanang Pratiwi Dwi Wulandari Rabbani, Mochamad Rafif Rahmat, Ayi Rizqi Rizaldi Hidayat RR. Ella Evrita Hestiandari Saifur Rohman Siahaan, Gracia Tiffany Sri Pujiyati Steven Solikin Sulaeman Martasuganda Suparman Sasmita Syamsul B. Agus Try Febrianto Vincentius P Siregar Wiliandi Setiawan Yusli Wardiatno Zulfathri Randhi