Muzakky, Ahnaf Farel (2024) Pengembangan Sistem Pengambilan Keputusan Aktivitas IUU Transshipment Dan Fishing Dengan Deteksi Massal Menggunakan Metode Anfis Serta Pemilihan Kapal Patroli. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Indonesia memiliki kekayaan sumber daya kelautan dan perikanan yang sangat beragam dan melimpah. Namun, kekayaan ini juga meningkatkan potensi terjadinya aktivitas ilegal di laut, seperti Illegal Transshipment (bongkar-muat ilegal) dan Illegal fishing. Aktivitas IUU (Illegal, Unreported, and Unregulated) Transshipment dan fishing ini dapat dideteksi melalui pemantauan data Automatic Identification System (AIS). Kapal yang terlibat dalam aktivitas ilegal ini sering menunjukkan anomali pada data navigasi mereka, yang dapat menjadi indikasi adanya pelanggaran regulasi kelautan dan perikanan. Namun, proses deteksi anomali pada kapal yang dilakukan satu per satu tidak efisien untuk memantau aktivitas ilegal di wilayah laut yang luas. Oleh karena itu, penelitian ini mengembangkan sistem pengambilan keputusan untuk mendeteksi IUU Transshipment dan fishing secara massal. Sistem ini terdiri dari empat sub�sistem: sub-sistem selector kapal untuk menyeleksi jenis kapal yang terlibat, sub-sistem Transshipment Selection untuk menyeleksi kapal-kapal yang diduga melakukan IUU Transshipment, sub-sistem Transshipment Decision untuk menentukan apakah kapal yang diduga melakukan IUU Transshipment benar-benar terlibat, dan sub-sistem fishing Decision untuk menentukan apakah kapal yang diduga melakukan IUU fishing benar-benar terlibat. Terakhir, ada sub-sistem pemilihan kapal patroli KKP (Kementerian Kelautan dan Perikanan) yang paling efisien untuk melakukan penindakan terhadap pelanggaran yang dilakukan oleh kapal. Sistem keseluruhan didesain menggunakan metode ANFIS (Adaptive Neuro-Fuzzy Inference System). Hasil validasi menunjukkan bahwa sistem ini mampu menghasilkan output yang sesuai dengan kondisi aktual, dengan akurasi sistem yang tergolong highly-accurate
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Indonesia has a wealth of very diverse and abundant marine and fisheries resources. However, this wealth also increases the potential for illegal activities at sea, such as Illegal Transshipment (illegal loading and unloading) and Illegal fishing. IUU (Illegal, Unreported, and Unregulated) Transshipment and fishing activities can be detected through Automatic Identification System (AIS) data monitoring. Vessels involved in these illegal activities often exhibit anomalies in their navigation data, which can be an indication of violations of maritime and fisheries regulations. However, the process of detecting anomalies on ships that is carried out one by one is inefficient for monitoring illegal activities in large sea areas. Therefore, this research develops a decision-making system to detect mass IUU transshipment and fishing. This system consists of four sub-systems: ship selector sub-system to select the type of ship involved, Transshipment Selection sub-system to select ships suspected of committing IUU Transshipment, Transshipment Decision sub-system to determine whether a ship is suspected of committing IUU Transshipment is actually involved, and the Fishing Decision sub-system is to determine whether vessels suspected of IUU fishing are actually involved. Finally, there is a sub-system for selecting the most efficient KKP (Ministry of Maritime Affairs and Fisheries) patrol vessels for taking action against violations committed by vessels. The overall system was designed using the ANFIS (Adaptive Neuro-Fuzzy Inference System) method. The validation results show that this system is able to produce output that corresponds to actual conditions, with system accuracy that is classified as highly accurate
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Automatic Identification System (AIS), Adaptive Network-Based Fuzzy Inference System (ANFIS), IUU Transshipment, IUU Fishing |
| Subjects: | V Naval Science > V Naval Science (General) |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Ahnaf Farel Muzakky |
| Date Deposited: | 25 Jul 2024 07:31 |
| Last Modified: | 03 Sep 2024 02:46 |
| URI: | http://repository.its.ac.id/id/eprint/108933 |
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