Damastuti, Natalia and Aisjah, Aulia Siti and Masroeri, Agoes (2020) Vessel Classifying and Trajectory Based on Automatic Identification System Data. In: International Conference on Science, Infrastructure Technology and Regional Development, 23-25 October 2020, South Lampung, Indonesia.
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Abstract
Nowadays, the development of the of Automatic Identification System (AIS) device has continuously increased. It was initially used to send information on the whereabouts of ships to avoid collisions, but with stored data, it is used for monitoring waters. Therefore, this study was carried out using AIS data to classify ships in Indonesian waters. Based on features such as length, width, and weight, it classified them into 9 types of vessels. The data mining process was used to characterize each type with the ensemble method. Furthermore, data processing was carried out to determine the ship's trajectory pattern. In this study, 80% of training data was used while the rest were testing data. The results showed that an accuracy value of 99.8% was obtained with a Root Mean Square Error (RMSE) value of 0.12. Keywords : Automatic Identification System, Classification, Vessel, Data mining, AIS, XG-Boost
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > Q Science (General) |
| Divisions: | Fakultas Ilmu Komputer > Sistem Informasi |
| Depositing User: | Repository Administrator |
| Date Deposited: | 24 May 2022 09:12 |
| Last Modified: | 24 May 2022 09:12 |
| URI: | http://repository.narotama.ac.id/id/eprint/1201 |
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