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All Journal Jurnal SPEKTRUM PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah Kursor JOIV : International Journal on Informatics Visualization Matrix : Jurnal Manajemen Teknologi dan Informatika Jurnal Teknoinfo Journal of Electrical, Electronics and Informatics Ulil Albab
Widyadi Setiawan
Electrical Engineering Department, Udayana University
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences

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Journal : JOIV : International Journal on Informatics Visualization

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Ship Trajectory Prediction Based on Spatial-temporal Data Using Long Short-Term Memory Setiawan, Widyadi; Linawati, Linawati; Widyantara, I Made Oka; Wiharta, Dewa Made; Asri, Sri Andriati; Pawana, I Wayan Adi Juliawan
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.3353

Abstract

The frequent exploitation of shipping lines by passengers increased traffic and exposed it to more significant dangers. Precise predictions for ship trajectory conditions at sea must be available to ensure safe navigation across the oceans. This article presents a trajectory prediction approach based on Long Short-Term Memory (LSTM) neural networks applied to time series Automatic Identification System (AIS) position data, expressed in spatial-temporal form. LSTM is highly suitable for ship trajectory predictions as it can capture long-term dependencies and spatial-temporal patterns existing in AIS data, since LSTM is targeted toward sequential data. The proposed model extracts ship trajectories from AIS data and utilizes an LSTM (Long Short-Term Memory) model to predict future ship movements based on historical patterns. The experiments demonstrate that it is effective in predicting where ships to navigate next, providing a valuable tool for enhancing traffic flow and improving navigation safety. The model with LSTM unit 500, tested on 3,478 ship trajectories, showed a median RMSE prediction error ranging from 0.0720 to 0.0841, with prediction M=8 coordinate a head having the highest error (0.0841) and M=2 and M=9 having the lowest (0.0720); the interquartile range (IQR) spanned from 0.0571 to 0.1006, and M=2 had the most outliers (302) while M=8 had the fewest (171), indicating varying prediction stability across different points. Despite these results, challenges remain in maintaining prediction stability across all points. Further optimization could enhance the model's performance and address these limitations by incorporating more complex spatial-temporal features or hybrid techniques.
Co-Authors A.A Ngurah Amrita Alfian Hadianto Antonius Ibi Weking Ardiansiah Ardiansiah Axel Adamma Diwanda Azra Ariel Azmir Bagus D. Cahyono Desi Ramayanti Dewa Gede Satria Bayu Putra Dewa Made Wiharta Dewa Ngakan Made Barel Dove Gandaria, Aaron Gerry Ian Duman Care Khrisne Dyana Arjana, I Gd. E. Duta Nugraha, I Putu Gede Sastra Utara Gede Sukadarmika Hilmy Jawas I Dewa Gde Bayu Wiranatha I Dewa Gede Aditya Pemayun I Dewa Gede Angga Prastika I G. A. K. Diafari Djuni Hartawan I Gede Dyana Arjana I Gede Dyana Arjana, I Gede I Gede Wiyoga Putra I Gusti Agung Adhi Waskita I Gusti Agung Komang Diafari Djuni Hartawan I Gusti Made Andi Dipayana I Ketut Ariek Astana Adi I Made Arsa Suyadnya I Made Martina Edi Putra I Made Oka Widyantara I N Satya Kumara I Nyoman Budiastra I Nyoman Setiawan I Putu E. Duta Nugraha I Putu Gede Krsna Yudha Dharma I Putu Hardy Sarjana I Putu Weda Suryawan I Wayan Darma Satika Ida Ayu Putu Intania Paramitha1 Ida Bagus A. Swamardika Issabelle M. Merry Jaime Luis da Costa Kevin Philip Komang Oka Saputra Komang Rio Adi Prasetya Limbong, Patrick Andreas Linawati Linawati M. Merry, Issabelle Made R. D. Prabawa Maharta Pemayun, A.A Gd. Maria Gusti Agung Ayu Permata Michael Angelo Vincensio Simon Muhamad Sony Pratama Ngurah Indra ER Ni Kadek Diah Parwati Ni Made Ary Esta Dewi Wirastuti Ni Putu Dina Rahmawati Ni Wayan Ernawati Novadianto Yudha Irawan Nyoman Putra Sastra Oktafiana Susanti, Baiq Dwinda Padwita Darma, I Made Angga Pande Ketut Sudiarta, Pande Ketut Patrick Andreas Limbong Pawana, I Wayan Adi Juliawan Permata Sari, Indah Ayu Philip, Kevin R. D. Prabawa, Made Rendi Gustina Riawanto Tambun Robbani Punggawa Arcapada Rukmi Sari Hartati Satriya Utama Sri Andriani Asri Sri Andriati Asri Sri Andriati Asri Sri Andriati Asri Sri Andriati Asri Sri Andriati Asri, Sri Andriati Sri Dianing Asri Sungkono, Gilberth Tjok Gede Indra Partha Vina Yuliani, Ni Putu Willy Sucipto Willy Susanto