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.

Original languageEnglish
Article number012049
JournalIOP Conference Series: Earth and Environmental Science
Volume830
Issue number1
DOIs
Publication statusPublished - 4 Oct 2021
Event5th International Conference on Science, Infrastructure Technology and Regional Development 2020, ICoSITeR 2020 - South Lampung, Virtual, Indonesia
Duration: 23 Oct 202025 Oct 2020

Keywords

  • AIS
  • Automatic Identification System
  • Classification
  • Data mining
  • Vessel
  • XG-Boost

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