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Acoustic Wave Propagation Patterns in the Ocean Column Fachri Ali Badihi; Sri Pujiyati; Ayi Rahmat; Steven Solikin; Muhammad Hisyam
Jurnal Segara Vol 18, No 3 (2022): December
Publisher : Politeknik Kelautan dan Perikanan Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/segara.v18i3.11453

Temperature and salinity play a role in the speed of sound and the process of sound propagation of acoustic waves in the water. Research on the propagation of sound waves in the ocean is a very interesting topic to do because it has many applications, including in underwater wireless communication systems and maritime security. This study aimed to analyze the propagation of acoustic waves in different water depths. The modeling was carried out with flat wave characteristics, in which the bathymetry characteristics of the seawater were ignored. In this ray path simulation, the frequency of 5.3Hz was used at 3 stations with different seawater depths in the Makassar Strait using temperature and salinity data downloaded from marine.coperniccus.eu data. The movement pattern of the acoustic waves was simulated using the Bellhop method. The ray tracing simulation results showed significant differences at the three locations. This was influenced by several factors, including the condition of the seawater environment, the placement of the transducer, the speed of sound, and the depth. Shallow seawater would show a more complicated ray path than deep seawater. The greater the angle of the half beam used, the greater the distance of the range of each beam of light will be so that the reflection of the resulting beam of light covers each column of seawater. The closer the distance between the resulting ray paths, the smaller the energy lost.

Autonomous Underwater Vehicle untuk Survei dan Pemantauan Laut Henry M. Manik; Agung D. Syakti; Jales Veva Jaya; Dony Apdillah; Steven Solikin; Angga Dwinovantyo; Rina Fajaryanti; Bagas O. Siahaan; Muhammad Sanubari
Jurnal Rekayasa Elektrika Vol 13, No 1 (2017)
Publisher : Universitas Syiah Kuala

AUV is an unmanned submersible platform to accomplish a mission. Side-scan sonar, Conductivity Temperature Depth (CTD), and underwater video camera are usually attached on AUV. These sensors were used for identifying seawater and seabed condition. Data acquired from a survey with an AUV in Kepulauan Riau processed by Neptus software. Side-scan sonar (SSS) visualization is compared to the video image. SSS signal visualization has a unique pattern that can be identified within the video image. Different substrate structure caused different signal visualization. The relation between the video image and SSS visualization can be used for identifying habitat benthic profile.

Pemrosesan Sinyal Data Sub-bottom Profiler Substrat Dasar Perairan Selat Lembeh Steven Solikin; Henry M. Manik; Sri Pujiyati; Susilohadi Susilohadi
Jurnal Rekayasa Elektrika Vol 13, No 1 (2017)
Publisher : Universitas Syiah Kuala

An accurate mapping of ocean seabed is needed to answer the challenges faced by the marine scientist today. Sub-bottom profiler present as one of the acoustics system which used to describe the sediment layer profile of the ocean bottom, as well as the thickness of the layer and the stratigraphy. The purpose of this research is to describe the 2D profile and to determine the value of the reflection coefficient of the sediment layers in Lembeh Strait, North Sulawesi. The reflection coefficient is necessary to be analyzed related to the seabed sediment grain size and type. The data acquisition carried out using Syqwest Stratabox sub-bottom profiler with the frequency of 10 kHz. FFT signal processing and bandpass filter are applied to relieve noise from main signals as well as to get better results. The results of data processing show that seafloor sediments have a value of the surface reflection coefficients which ranged between 0.1168 until 0.7938 with type iron smooth sand.

Identifikasi dan Analisis Nilai Hamburbalik Objek Dasar Di Perairan Punggur Batam Bryan Felix Simanjuntak; Sri Pujiyati; Steven Solikin; Muhammad Zainuddin Lubis
Buletin Oseanografi Marina Vol 12, No 3 (2023): Buletin Oseanografi Marina
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/buloma.v12i3.52393

Deteksi objek dasar perairan merupakan proses analisa objek yang menggunakan kemampuan teknologi sonar. Side scan sonar (SSS) adalah alat yang menggunakan komponen satu beam (Single beam) yang dapat menampilkan citra dalam bentuk dua dimensi (2D). Tujuan dari penelitian ini adalah menganalisis dan mendeteksi objek dasar di Perairan Punggur Batam. Penggunaan data side scan sonar sangat efisien dalam mengidentifikasi Perairan Punggur Batam. Data side scan sonar dengan format Xtf diproses dengan menggunakan koreksi radiometrik dan geometrik melalui perangkat lunak SonarWiz 7 untuk mendapatkan klasifikasi citra. Proses ekstraksi data menggunakan perangkat lunak SeiSee 2.2 untuk menampilkan nilai amplitudo dan waktu. Trace diambil sesuai nomor ping target. Trace data dikonversi ke dalam format txt atau xls kemudian data trace diinput ke dalam perangkat lunak Matlab r2017a untuk menampilkan grafik amplitudo (mV). Analisis hamburbalik menggunakan perhitungan logaritma yaitu 20Log10 (Vt/V0) dengan Vt merupakan dominan dan V0 amplitudo maksimum. Berdasarkan hamburbalik SSS di perairan Punggur Batam diperoleh 6 target yang memiliki nilai hamburbalik -3,32 dB, -5,71 dB, -1,13 dB, -6,81 dB, -4,86 dB, dan -3,74 dB. Nilai hamburbalik digunakan untuk menduga jenis target yang ada di perairan Punggur, yaitu karang besar, karang sedang, batu besar, batu sedang, serta batu cukup besar. Besar kecilnya nilai hamburbalik yang didapatkan dipengaruhi oleh amplitudo target. Detection of underwater objects is an object analysis process that uses the capabilities of sonar technology. Side scan sonar is a tool that uses Single beam which can display images in two dimensions (2D). The purpose of this study is to analyze and detect objects on the bottom of the waters. The use of side scan sonar data is very efficient in identifying Punggur Batam Waters. Side scan sonar (SSS) data in Xtf format was processed using radiometric and geometric corre ctions with SonarWiz 7 software to obtain image classifications. The data extraction process used SeiSee 2.2 software to show the amplitude and time values. Traces were taken based on the target ping number. The trace data were converted into txt or xls format then the trace data was inputted into the Matlab r2017a software to show an amplitude (mV) graph. The backscatter analysis used a logarithmic calculation, 20Log10 (Vt/V0) with Vt being the dominant and V0 being the maximum amplitude. Based on the SSS backscattering in the waters of Punggur Batam we got 6 targets which had backscatter values about -3.32 dB, -5.71 dB, -1.13 dB, -6.81 dB, -4.86 dB, and -3.74 dB. The backscatter value is used to estimate the types of targets in Punggur waters, namely large corals, medium corals, large rocks, medium rocks, and quite large rocks. The size of the backscatter value was influenced by the target amplitude.

Combining Two Classification Methods for Predicting Jakarta Bay Seabed Type Using Multibeam Echosounder Data Steven Solikin; Angga Dwinovantyo; Henry Munandar Manik; Sri Pujiyati; Susilohadi Susilohadi
Journal of Applied Geospatial Information Vol 7 No 2 (2023): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v7i2.6363

Classification of seabed types from multibeam echosounder data using machine learning techniques has been widely used in recent decades, such as Random Forest (RF), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Nearest Neighbor (NN). This study combines the two most frequently used machine learning techniques to classify and map the seabed sediment types from multibeam echosounder data. The classification model developed in this study is a combination of two machine learning classification techniques, namely Support Vector Machine (SVM) and K-Nearest Neighbor (K-NN). This classification technique is called SV-KNN. Simply, SV-KNN adopts these two techniques to carry out the classification process. The SV-KNN technique begins with determining test data by specifying support vectors and hyperplanes, as was done on the SVM method, and executes the classification process using the K-NN. Clay, fine silt, medium silt, coarse silt, and fine sand are the five main classes produced by SVKNN. The SV-KNN method has an overall accuracy value of 87.38% and a Kappa coefficient of 0.3093.

Autonomous Underwater Vehicle untuk Survei dan Pemantauan Laut Henry M. Manik; Agung D. Syakti; Jales Veva Jaya; Dony Apdillah; Steven Solikin; Angga Dwinovantyo; Rina Fajaryanti; Bagas O. Siahaan; Muhammad Sanubari
Jurnal Rekayasa Elektrika Vol 13, No 1 (2017)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v13i1.5964

AUV is an unmanned submersible platform to accomplish a mission. Side-scan sonar, Conductivity Temperature Depth (CTD), and underwater video camera are usually attached on AUV. These sensors were used for identifying seawater and seabed condition. Data acquired from a survey with an AUV in Kepulauan Riau processed by Neptus software. Side-scan sonar (SSS) visualization is compared to the video image. SSS signal visualization has a unique pattern that can be identified within the video image. Different substrate structure caused different signal visualization. The relation between the video image and SSS visualization can be used for identifying habitat benthic profile.

Pemrosesan Sinyal Data Sub-bottom Profiler Substrat Dasar Perairan Selat Lembeh Steven Solikin; Henry M. Manik; Sri Pujiyati; Susilohadi Susilohadi
Jurnal Rekayasa Elektrika Vol 13, No 1 (2017)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v13i1.6060

An accurate mapping of ocean seabed is needed to answer the challenges faced by the marine scientist today. Sub-bottom profiler present as one of the acoustics system which used to describe the sediment layer profile of the ocean bottom, as well as the thickness of the layer and the stratigraphy. The purpose of this research is to describe the 2D profile and to determine the value of the reflection coefficient of the sediment layers in Lembeh Strait, North Sulawesi. The reflection coefficient is necessary to be analyzed related to the seabed sediment grain size and type. The data acquisition carried out using Syqwest Stratabox sub-bottom profiler with the frequency of 10 kHz. FFT signal processing and bandpass filter are applied to relieve noise from main signals as well as to get better results. The results of data processing show that seafloor sediments have a value of the surface reflection coefficients which ranged between 0.1168 until 0.7938 with type iron smooth sand.

IDENTIFIKASI BERBAGAI JENIS SAMPAH LAUT DAN PENGELOLAANNYA BERSAMA MASYARAKAT PULAU TIDUNG, KEPULAUAN SERIBU Sri Pujiyati; Endang Sunarwati Srimariana; Dea Fauzia Lestari; Riza Aitiando Pasaribu; Mochamad Tri Hartanto; Nyoman Metta Natih; Rastina Rastina; Steven Solikin; Erwin Maulana
Panrita Abdi - Jurnal Pengabdian pada Masyarakat Vol. 8 No. 1 (2024): Jurnal Panrita Abdi - Januari 2024
Publisher : LP2M Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/pa.v8i1.22001

Tidung Island is one of the islands in the Seribu Island area which has marine tourism destinations. To declare the achievement of SDGs no. 6 (Clean water and sanitation) and 14 (Life Below Water), then one of the community service activities (PPM) that can be done is cleaning garbage in the coastal areas. This activity aims to be directly involved in cleaning up garbage on Tidung Island. The method used was going directly to the field as well as conducting direct observations and interviews to find out the sources and types of existing waste and waste management that is already running. The result of this PPM activity is a clean beach on Tidung Island. This activity was carried out to get Tidung Island’s coast clean and healthy so that SDGs no. 6 and 14 can be reached. The results of community service activities show that the community is enthusiastic to carry out waste management independently and with related officers to create the Tidung Island area as marine tourism. --- Pulau Tidung adalah salah satu pulau di daerah Kepulauan Seribu yang memiliki destinasi wisata bahari. Dalam rangka mencanangkan capaian SDGs no. 6 (Clean water and sanitation) dan 14 (Life Below Water) maka salah satu kegiatan pengabdian pada masyarakat yang dapat dilakukan adalah pembersihan sampah di wilayah pesisir. Kegiatan ini bertujuan untuk terlibat langsung dalam membersihkan sampah di Pulau Tidung. Metode yang digunakan adalah turun langsung di lapangan sekaligus melakukan pengamatan langsung dan wawancara untuk mengetahui sumber dan macam sampah yang ada serta pengelolaan sampah yang sudah berjalan. Hasil berkegiatan PPM ini yaitu membersihkan pantai di Pulau Tidung. Kegiatan ini dilakukan untuk mendapatkan pantai Pulau Tidung yang bersih dan sehat sehing-ga dapat tercapainya SDGs no. 6 dan 14. Hasil kegiatan pengabdiam masyarakat menunjukkan masyarakat bersemangat untuk melakukan pengelolaan sampah secara mandiri maupun bersama petugas terkait untuk menciptakan kawasan Pulau Tidung sebagai wisata bahari.

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