Setyaningrum, Intan Mey (2023) Pengembangan Sistem Identifikasi IUU Transshipment Saat Terjadi Anomali Data AIS Menggunakan Adaptive Neuro Fuzzy Inference System (ANFIS) dengan Mengakomodasi Kecepatan Angin. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Indonesia merupakan negara maritim terbesar dengan luas lautannya yang mencapai 3.544.743,9 km2. Dengan luasnya wilayah lautan Indonesia tersebut, terdapat aktivitas ilegal yang sangat merugikan dikarenakan kurangnya pengawasan contohnya transshipment ilegal. Beberapa teknologi telah dikembangkan untuk memantau pergerakan kapal, termasuk identifikasi pelanggaran IUU transshipment, diantaranya AIS (Automatic Identification System), VTS (Vessel Traffic System), dan perangkat radar. Dalam kondisi nyata, di saat tertentu kapal akan berada tidak sesuai dengan jalurnya (anomaly data trajectory). Hal ini mengakibatkan kecurigaan dilakukannya transshipment. AIS hanya mendeteksi posisi dari kapal tidak mendeteksi cuaca di sekitar kapal, padahal deteksi cuaca disekitar kapal yang berlayar seperti kecepatan angin sangat penting. Jika kecepatan angin di sekitar kapal yang berlayar besar, maka akan kecil kemungkinan terjadi IUU transshipment. Penelitian ini dilakukan untuk merancang sistem pengambilan keputusan berbasis data AIS untuk identifikasi terjadinya IUU transshipment saat terjadi anomali data trayektori menggunakan metode Adaptive Neuro Fuzzy Inference System (ANFIS) dengan mengakomodasi kecepatan angin. Sistem terdiri dari 3 sub-sistem yaitu sub-sistem anomali, sub-sistem selection, dan sub-sistem decision yang ketiganya menggunakan metode ANFIS. Data pada penelitian diperoleh dari website marinetraffic.com, Marine Reliability and Safety Laboratory, dan data online BMKG. Hasil pengujian menunjukkan nilai akurasi untuk sistem identifikasi IUU transshipment sebesar 83,46 %.
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Indonesia is the largest maritime country with a sea area of 3.544.743,9 km2. With the vast territory of Indonesia's oceans, there are illegal activities that are very detrimental due to lack of supervision, for example transshipment illegal. Several technologies have been developed to monitor ship movements, including the identification of IUU violations transshipment, including AIS (Automatic Identification System), VTS (Vessel Traffic System), and radar devices. In real conditions, at certain times the ship will be not according to course (anomaly data trajectory). This led to suspicion of doing sotransshipment. AIS only detects the position of the ship does not detect the weather around the ship, even though weather detection around sailing ships such as wind speed is very important. If the wind speed around the sailing ship is large, there will be less possibility of IUU transshipment. This research was conducted to design a decision-making system based on AIS data to identify the occurrence of IUU transshipment when an anomaly trajectory data occurs using the method Adaptive Neuro Fuzzy Inference System (ANFIS) to accommodate wind speed. The system consists of 3 sub-systems namely anomaly sub-system, selection sub-system, and decision sub-system all three using the ANFIS method. The data in this study were obtained from website marinetraffic.com, Marine Reliability and Safety Laboratory, and online data BMKG. The test results show the accuracy value for the identification system IUU transshipment is 83,46%.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Adaptive Neuro Fuzzy Inference System (ANFIS), Anomali Data, Automatic Identification System (AIS), IUU Transshipment, Data Anomaly |
| Subjects: | V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering > VM293 Shipping--Indonesia--Safety measures |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Intan Mey Setyaningrum |
| Date Deposited: | 29 Jul 2023 06:09 |
| Last Modified: | 29 Jul 2023 06:09 |
| URI: | http://repository.its.ac.id/id/eprint/99683 |
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