Echogram Image Analysis for Pelagic Fish School Classification in Bungus Waters, West Sumatra
Article Sidebar
-
Bungus, fish school, kurtosis, skewness, volume backscattering strength
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.
Full text article
References
Achmadi A, Hestirianoto T, & Manik HM. 2015. Deteksi schooling ikan pelagis dengan metode hidroakustik di perairan Teluk Palu, Sulawesi Tengah. Jurnal Teknologi Perikanan dan Kelautan, 5(2), 129-137. https://doi.org/10.24319/jtpk.5.129-137
Bafagih A. 2015. Analisis potensi perikanan pelagis kecil di Kota Ternate. Jurnal Ilmiah Agribisnis dan Perikanan, 8(2): 20-21. https://doi.org/10.29239/j.agrikan.8.2.20-27
Diner N, Weill A, Coail JY, Coudevil JM. 1989. “Ines-Movies”: A new acoustic data acquisition and processing system. J Mar Sci, 45:255-267.
Farhan M, Manik HM, Hestirianoto T. 2022. Pengukuran nilai target strength dan acoustic fish density di perairan Pulau Tidung, Kepulauan Seribu. Jurnal Teknologi Perikanan dan Kelautan, 13(2): 175-186. https://doi.org/10.24319/jtpk.13.175-186
Fauziyah, Jaya I. 2005. Pengembangan perangkat lunak acoustic descriptor analyzer (ADA-versi 2004) untuk identifikasi kawanan ikan pelagis. Jurnal Ilmu-ilmu Perairan dan Perikanan Indonesia, 11 (2): 87-92.
Fauziyah, Hartoni, Agussalim A. 2010. Karakteristik shoaling ikan pelagis menggunakan data akustik split beam di perairan Selat Banga pada musim timur. Ilmu Kelautan, 15(1):17-22.
Hutauruk RM dan Rengi P. 2017. Penanganan pendaratan hasil tangkapan di Pelabuhan Perikanan Samudera Bungus Provinsi Sumatera Barat. Jurnal Perikanan dan Kelautan, 22(2): 57-64.
Lu HJ, Lee KT. 1995. Species identification of fish shoals echograms by an echosignal image processing system. J Fish Res, 24(2): 99-111. https://doi.org/10.1016/0165-7836(94)00368-7
Manik HM dan Ma’mun A. 2009. Rancang bangun sistem informasi data hidroakustik berbasis web. Seminar Nasional Aplikasi Teknologi Informasi. 2009 Jun 20; Yogyakarta, Indonesia. Yogyakarta: hlm 12-16.
Muhiddin AH, Jaya I & Hestirianoto T. 2007. Identifikasi Kawanan Ikan Lemuru dari Data Hidroakustik dengan Metode Jaringan Syaraf Tiruan. TORANI Journal of Fisheries and Marine Science, 17(3): 181-192.
Natsir M, Sadhotomo B, Wudianto. 2005. Pendugaan biomassa ikan pelagis di perairan Teluk Tomini dengan metode akustik bim terbagi. Jurnal Penelitian Perikanan Indonesia. 11(6): 101-107. https://doi.org/10.15578/jppi.11.6.2005.101-107
Nontji A. 2008. Plankton Laut. Jakarta (ID): Lembaga Ilmu Pengetahuan Indonesia (LIPI).
Reid, D.G., and E. Simmonds. 1993. Image Analysis Techniques For The Study Of Fish School Structure From Acoustic Survey Data. Can. J. Fish. Aquat. Sci, 50: 886-893. https://doi.org/10.1139/f93-102
Rudin MJ, Irnawati R & Rahmawati A. 2017. Perbedaan hasil tangkapan bagan tancap dengan menggunakan lampu cfl dan led dalam air (leda) di perairan Teluk Banten. Jurnal Perikanan, 7(2): 167-180. https://doi.org/10.33512/jpk.v7i2.2686
Santoso S. 2010. Statistik Multivariat: Konsep dan Aplikasi dengan SPSS. Jakarta (ID): Penerbit Elex Media Komputindo.
Santoso S. 2017. Statistik Multivariat dengan SPSS. Jakarta (ID): Penerbit Elex Media Komputindo.
Setiadi B, Brown A, Bustari. 2015. Distribution target strength in waters bengkalis demersal fish province riau. JOMFAPERIKA, 2(2):1-13.
Shalsadilla N, Martha S, Perdana H, Satyadewi N, Sulistianingsih E. 2023. Penentuan jumlah cluster optimum menggunakan davies bouldin index dalam pengelompokan wilayah kemiskinan di Indonesia. Statistika. 23(1): 63-72. https://doi.org/10.29313/statistika.v23i1.1743
Siregar ESY, Siregar VP, Agus SB. 2018. Analisis daerah penangkapan ikan tuna sirip kuning (Thunnus albacares) di perairan Sumatera Barat berdasarkan model GAM. Jurnal Ilmu Dan Teknologi Kelautan Tropis, 10(2), 501-516. https://doi.org/10.29244/jitkt.v10i2.21908.
Weihs, D. 1973. Hydromechanics of Fish Schooling. Nature, 241 : 290–291.
Authors
Copyright (c) 2025 Jovian Lansky, Steven Solikin, Sri Pujiyati, Totok Hestirianoto
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Ilmu dan Teknologi Kelautan Tropis i is an open-access journal, meaning that all content is freely available without charge to the user or their institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without needing to request prior permission from the publisher or the author.
All articles published by Jurnal Ilmu dan Teknologi Kelautan Tropis are licensed under the Creative Commons Attribution 4.0 International License. This allows for unrestricted use, distribution, and reproduction in any medium, provided proper credit is given to the original authors.
Authors submitting manuscripts should understand and agree that the copyright of published manuscripts is retained by the authors. Copyright encompasses the exclusive rights of authors to reproduce, distribute, and sell any part of the journal articles in all forms and media. Reproduction of any part of this journal, its storage in databases, and its transmission by any form or media is allowed without written permission from Jurnal Ilmu dan Teknologi Kelautan Tropis.