Pengembangan Ship Route Planner Berdasarkan Performa Seakeeping Kapal: Studi Kasus Kapal Small LNG Pelayaran Wilayah Indonesia Timur

Caramoy, Steven (2025) Pengembangan Ship Route Planner Berdasarkan Performa Seakeeping Kapal: Studi Kasus Kapal Small LNG Pelayaran Wilayah Indonesia Timur. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia, sebagai salah satu anggota G-20, berkesempatan menjadi tuan rumah Konferensi Tingkat Tinggi (KTT) dan Presidensi G-20 ke-22. Dalam forum ini, tiga isu utama diangkat, yaitu transisi energi berkelanjutan, transformasi digital, dan arsitektur kesehatan global. Salah satu upaya transisi energi yang dilakukan Indonesia adalah peralihan pembangkit listrik dari bahan bakar minyak ke LNG (Liquified Natural Gas). Untuk memenuhi kebutuhan pasokan LNG ke pembangkit listrik di wilayah Indonesia Timur yang efisien dan ekonomis, diperkenalkan skema kapal LNG skala kecil (small LNG) yang berfungsi sebagai moda transportasi, storage dan regasification. Namun, tantangan muncul ketika kapal small LNG beroperasi di perairan Indonesia Timur, yaitu kemampuan seakeeping yang kurang optimal saat menghadapi gelombang tinggi. Untuk mengatasi permasalahan ini, penelitian ini mengembangkan software ship route planner yang dirancang untuk menemukan rute terpendek dan teraman bagi kapal. Pengembangan perangkat lunak ini menggunakan data kapal LNG DTP-04 sebagai studi kasus. Data tersebut dianalisis untuk mendapatkan data gerakan kapal, yaitu roll, heave, dan pitch, yang kemudian digunakan sebagai data pelatihan dalam model ANN (Artificial Neural Network) untuk memprediksi gerakan kapal. Software ship route planner mengombinasikan algoritma Dijkstra dengan model ANN untuk menghasilkan rute terpendek dan teraman. Hasil pengujian menunjukkan bahwa software mampu memenuhi kebutuhan fungsional dan memprediksi rute dengan margin error kurang dari 10% untuk gerakan roll, heave, dan pitch dibandingkan dengan metode frequency domain. Dengan demikian, penggunaan software ship route planner pada kapal LNG DTP-04 dapat menentukan rute pelayaran yang aman dan efisien di wilayah Indonesia Timur.
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Indonesia, as a member of the G-20, had the opportunity to host the 22nd G-20 Summit and Presidency. This forum highlighted three main issues: sustainable energy transition, digital transformation, and global health architecture. One of Indonesia's efforts in the energy transition is shifting power generation from oil-based fuel to LNG (Liquefied Natural Gas). To meet the LNG supply needs for power plants in Eastern Indonesia, a small-scale LNG ship (small LNG) scheme was introduced, functioning as both storage and regasification units. However, challenges arise when small LNG ships operate in Eastern Indonesian waters, particularly their suboptimal seakeeping capabilities in high-wave conditions. To address this issue, this research developed a ship route planner software designed to identify the shortest and safest routes for the ships. The software development utilized data from the LNG DTP-04 ship as a case study. This data was analyzed to obtain ship motion parameters, including roll, heave, and pitch, which were subsequently used as training data for an Artificial Neural Network (ANN) model to predict ship movements. The ship route planner software combines the Dijkstra algorithm with the ANN model to determine the shortest and safest routes. Testing results showed that the software effectively meets functional requirements and predicts routes with a margin of error of less than 10% for roll, heave, and pitch movements compared to calculations using the frequency domain method. Consequently, the LNG DTP-04 ship can navigate Eastern Indonesian waters safely and with time efficiency.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	LNG DTP-04, Seakeeping, Artificial Neural Network, Rute, Route
Subjects:	V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Faculty of Marine Technology (MARTECH) > Naval Architecture and Shipbuilding Engineering > 36101-(S2) Master Thesis
Depositing User:	Steven Caramoy
Date Deposited:	03 Feb 2025 08:54
Last Modified:	03 Feb 2025 08:54
URI:	http://repository.its.ac.id/id/eprint/117987

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