KLASIFIKASI RAMBU LALU LINTAS MENGGUNAKAN DECISION TREE J48 DAN LOCAL BINARY PATTERN - Tanuwidjaya, Kevin; -, Ericson; Hakim, Lukman (JITTER : Jurnal Ilmiah Teknologi dan Komputer, 2022)
Automatic steering technology or autopilot in cars is developing rapidly. This feature makes it easier for the driver because the car can run according to the program directions. The driver of course can still take control of the car manually as desired, so it is possible for the driver to violate traffic signs, whether intentionally or not. This study seeks to create a traffic sign recognition system that can help reduce violations committed by drivers knowingly. The test is carried out using a combination of the Local Binary Pattern algorithm as feature extraction and Decision Tree J48 algorithm as a classification system to recognize traffic signs. It is hoped that this research can provide an overview of the combined ability of these two algorithms in classifying types of traffic signs.