Damastuti, Natalia and Aisjah, Aulia Siti and Masroeri, Agoes A (2019) Classification of Ship-Based Automatic Identification Systems Using K-Nearest Neighbors. In: 2019 International Seminar on Application for Technology of Information and Communication (iSemantic),, 21-22 Sept. 2019, Semarang, Indonesia.
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Abstract
One of vessel monitoring systems which employs predetermined equipment to discover the movements and activities of vessels is AIS (Automatic Identification System). AIS contains the ship data either static (ship name, ship size, sailing time) or dynamic data (ship speed, rate of turn, ship heading). The ship tracking information system can be accessed by public, but manual monitoring will be difficult to do, given that data is increasingly heterogeneous and complex as well as its volumes increase exponentially. As a result, a more efficient method of data mining and processing are needed. In this study, k-NN algorithm is applied with the aim of classifying ships sailing in Indonesian waters. The algorithm is tested on real time AIS database using k-NN and the neighborhood component analysis (NCA). The result shows that NCA,KNN has higher accuracy than using k-NN on original classifier. Keywords——Vessel; k-NN; AIS; Neighborhood component analysis; Data Mining
| 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: | 25 May 2022 01:13 |
| Last Modified: | 25 May 2022 01:13 |
| URI: | http://repository.narotama.ac.id/id/eprint/1202 |
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