Oktyarini, Tiyas (2021) Perancangan Model Prediksi Warna Mobil Berbasis Histogram Warna dengan K-Nearest Neighbor untuk Mendukung Smart Traffic Monitoring System. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT Each vehicle has its own identity. Vehicle information recognition is part of an intelligent transportation system based on visual information collected by cameras which is intended for traffic monitoring with an emphasis on traffic events caused by cars. A car is a vehicle that has a variety of colors. The technology allows the identification of car colors based on the color histogram with the help of computers on the image of the car. This study aims to predict car color using the K-Nearest Neighbor (KNN) algorithm to support the Smart Traffic Monitoring System. The K-Nearest Neighbor (KNN) algorithm is a classification method for a set of data based on learning data that has been classified previously. K-Nearest Neighbor is a method that is easy to implement by only setting one parameter k. Keywords: Car Color, Color Histogram, K-Nearest Neighbor.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 27 Mar 2021 03:52 |
| Last Modified: | 27 Mar 2021 03:52 |
| URI: | http://eprints.uty.ac.id/id/eprint/7214 |
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