DOI: https://doi.org/10.14710/jil.22.3.667-671

Pemodelan Kesesuaian Habitat Ikan Cakalang Menggunakan Penginderaan Jauh di Perairan Selatan Jawa Barat – Banten

Research Oganisation for Earth Sciences and Maritime , National Institute of Aeronautics and Space, Indonesia

Received: 14 Jul 2023; Revised: 15 Nov 2023; Accepted: 6 Jan 2023; Available online: 9 Mar 2024; Published: 28 Mar 2024.
Editor(s): Budi Warsito

Citation Format:
Abstract
Pemodelan kesesuaian habitat merupakan hal yang sangat penting dalam proses perencanaan pengelolaan sumber daya perikanan laut di masa depan. Kondisi lingkungan suatu perairan mempengaruhi habitat ikan cakalang. Penelitian ini bertujuan untuk mengevaluasi model kesesuaian habitat ikan cakalang di perairan selatan Jawa Barat – Banten. Data suhu permukaan laut dan konsentrasi klorofil-a digunakan dalam pemodelan ini diperoleh dari citra satelit MODIS periode Desember 2018 hingga November 2019. Data lokasi tangkapan cakalang diperoleh dari laporan tangkapan. Pemodelan ini dijalankan menggunakan software MaxEnt. Suhu permukaan laut mempengaruhi model pada rentang 28,3 – 29,2 °C untuk musim barat dan 24,0 – 28,5 °C untuk musim timur. Model mendapat pengaruh konsentrasi klorofil-a pada rentang 0 – 0,1 mg/m3 baik pada musim barat maupun musim timur. Hasil pemodelan menunjukkan kinerja yang sangat baik dengan tingkat akurasi mencapai 0,84 untuk musim barat dan 0,92 untuk musim timur.
Fulltext View|Download
Keywords: MODIS, MaxEnt, cakalang

Article Metrics:

Article Info
Section: Research Article
Language : ID
Recent articles
Toxicity Reduction of Antiseptic Triclocarban by a Newly Isolated Strain Sphingobacterium sp. MC43 Mobilitas Merkuri pada Limbah Bekas Tambang Pengolahan Emas: Studi Kasus di Selogiri, Wonogiri, Jawa Tengah Studi Karakteristik Fisika Tanah Zona Perakaran dan Produksi Tanaman Kopi (Coffea sp.) di Kecamatan Wajak, Kabupaten Malang More recent articles
Most cited articles
PERBAIKAN KUALITAS AIR LIMBAH DOMESTIK DENGAN FITOREMEDIASI MENGGUNAKAN KOMBINASI BEBERAPA GULMA AIR: STUDI KASUS KOLAM RETENSI TALANG AMAN KOTA PALEMBANG Studi Pendahuluan Cemaran Air Limbah Rumah Potong Hewan di Kota Mataram IDENTIFIKASI KEMISKINAN AIR DI DAERAH ALIRAN SUNGAI CITARUM HULU: KASUS DAERAH BANDUNG RAYA Evaluasi Penerapan Program Adiwiyata Untuk Membentuk Perilaku Peduli Lingkungan di Kalangan Siswa (Kasus: SMA Negeri 9 Tangerang Selatan dan MA Negeri 1 Serpong) Menakar Kapasitas Adaptasi Perubahan Iklim Petani Padi Sawah (Kasus Kabupaten Pasuruan Jawa Timur) More cited articles
  1. Alabia, Irene, Sei-Ichi Saitoh, Robinson Mugo, Hiromichi Igarashi, Yoichi Ishikawa, Norihisa Usui, Kamachi Masafumi, Toshiyuki Awaji, and Masaki Seito. 2015. “Seasonal Potential Fishing Ground Prediction of Neon Flying Squid (Ommastrephes Bartramii) in the Western and Central North Pacific.” Fisheries Oceanography 24:190–203. doi: 10.1111/fog.12102
  2. Azzahra, Annisa Nazmi, Clara Avila Dea Permata, and Nabilla Akhirta. 2017. “Pemetaan Potensi Penangkapan Ikan Cakalang Di Perairan Sulawesi Mapping of Potential Capture of Skipjack Fish in Sulawesi Waters.” Seminar Nasional Penginderaan Jauh 331–39
  3. Coletto, Juliano, Marcelo de Pinho, and Lauro Madureira. 2018. “Operational Oceanography Applied to Skipjack Tuna (Katsuwonus Pelamis) Habitat Monitoring and Fishing in South-Western Atlantic.” Fisheries Oceanography 28. doi: 10.1111/fog.12388
  4. Druon, Jean-Noël, Emmanuel Chassot, Hilario Murua, and Jon Lopez. 2017. “Skipjack Tuna Availability for Purse Seine Fisheries Is Driven by Suitable Feeding Habitat Dynamics in the Atlantic and Indian Oceans.” Frontiers in Marine Science 4:315. doi: 10.3389/fmars.2017.00315
  5. Druon, Jean-Noel, Emmanuel Chassot, Hilario Murua, and María Soto. 2016. “Preferred Feeding Habitat of Skipjack Tuna in the Eastern Central Atlantic and Western Indian Oceans: Relations with Carrying Capacity and Vulnerability to Purse Seine Fishing.”
  6. Firdaus, Maulana. 2018. “Profil Perikanan Tuna Dan Cakalang Di Indonesia.” MARINA 4(1):23–32
  7. Fournier, Alice, Morgane Barbet-Massin, Quentin Rome, and Franck Courchamp. 2017. “Predicting Species Distribution Combining Multi-Scale Drivers.” Global Ecology and Conservation 12:215–26. doi: https://doi.org/10.1016/j.gecco.2017.11.002
  8. Guisan, A., & Thuiller, W. (2005). Predicting species distribution: Offering more than simple habitat models. Ecology Letters, 8, 993–1009. https://doi.org/10.1111/j.1461-0248.2005.00792.x
  9. Hosmer, David W., and Stanley Lemeshow. 2010. Applied Logistic Regression Second Edition. New York: John Wiley & Sons, Inc
  10. Jatmiko, Irwan, Raymon Zedta, Maya Agustina, and Bram Setyadji. 2019. “Genetic Diversity and Demography of Skipjack Tuna (Katsuwonus Pelamis) In Southern and Western Part of Indonesian Waters.” ILMU KELAUTAN: Indonesian Journal of Marine Sciences 24:61–68. doi: 10.14710/ik.ijms.24.2.61-68
  11. KKP. 2020a. Laporan Data Log Book Perikanan Tangkap Tahun 2020. Kementerian Kelautan dan Perikanan
  12. KKP. 2020b. Laporan Kinerja Kementerian Kelautan Dan Perikanan
  13. Lan, Kuo-Wei, Teruhisa Shimada, Ming-An Lee, Nan-Jay Su, and Yi Chang. 2017. “Using Remote-Sensing Environmental and Fishery Data to Map Potential Yellowfin Tuna Habitats in the Tropical Pacific Ocean.” Remote Sensing 9(5). doi: 10.3390/rs9050444
  14. Mugo, Robinson, Sei-Ichi Saitoh, AKIRA NIHIRA, and TADAAKI KUROYAMA. 2010. “Habitat Characteristics of Skipjack Tuna (Katsuwonus Pelamis) in the Western North Pacific: A Remote Sensing Perspective.” Fisheries Oceanography 19:382–96. doi: 10.1111/j.1365-2419.2010.00552.x
  15. Peterson, Andrew, Monica Papes, and Muir Eaton. 2007. “Transferability and Model Evaluation in Ecological Niche Modeling: A Comparison of GARP and Maxent.” Ecography 30:550–60. doi: 10.1111/j.0906-7590.2007.05102.x
  16. Phillips, Steven J., Robert P. Anderson, Miroslav Dudík, Robert E. Schapire, and Mary E. Blair. 2017. “Opening the Black Box: An Open-Source Release of Maxent.” Ecography 40(7):887–93. doi: 10.1111/ecog.03049
  17. Phillips, Steven J., Robert P. Anderson, and Robert E. Schapire. 2006. “Maximum Entropy Modeling of Species Geographic Distributions.” Ecological Modelling 190(3):231–59. doi: https://doi.org/10.1016/j.ecolmodel.2005.03.026
  18. Pundoko, Sandria Stephanie, Hens Onibala, and Agnes T. Agustin. 2014. “Perubahan Komposisi Zat Gizi Ikan Cakalang Katsiuwonus Pelamis. L Selama Proses Pengolahan Ikan Kayu.” Jurnal Media Teknologi Hasil Perikanan 2(1):9–14
  19. Sukresno, Bambang, Agus Hartoko, Budi Sulistyo, and Subiyanto. 2015. “Empirical Cumulative Distribution Function (ECDF) Analysis of Thunnus.Sp Using ARGO Float Sub-Surface Multilayer Temperature Data in Indian Ocean South of Java.” Procedia Environmental Sciences 23:358–67. doi: https://doi.org/10.1016/j.proenv.2015.01.052
  20. Yanti Siregar, Emma, Vincentius Siregar, and Syamsul Agus. 2018. “Fishing Ground Analysis of Yellowfin Tuna (Thunnus Albacares) in West-Sumatera Waters Based on Gam Model.” Jurnal Ilmu Dan Teknologi Kelautan Tropis 10:501. doi: 10.29244/jitkt.v10i2.21908
  21. Yen, kuo-wei, Hsueh-Jung Lu, Yi Chang, and Ming-An Lee. 2012. “Using Remote-Sensing Data to Detect Habitat Suitability for Yellowfin Tuna in the Western and Central Pacific Ocean.” International Journal of Remote Sensing - INT J REMOTE SENS 33:7507–22. doi: 10.1080/01431161.2012.685973
  22. Zainuddin, Mukti, Aisjah Farhum, Safruddin Safruddin, Muhammad Banda Selamat, Sudirman Sudirman, Nurjannah Nurdin, Mega Syamsuddin, Muhammad Ridwan, and Sei Ichi Saitoh. 2017. “Detection of Pelagic Habitat Hotspots for Skipjack Tuna in the Gulf of Bone-Flores Sea, Southwestern Coral Triangle Tuna, Indonesia.” PLoS ONE 12(10). doi: 10.1371/journal.pone.0185601

Last update:

No citation recorded.

Last update: 2024-11-21 23:56:33

No citation recorded.