KLASIFIKASI RAMBU LALU LINTAS MENGGUNAKAN DECISION TREE J48 DAN LOCAL BINARY PATTERN

  • Kevin Tanuwidjaya Student
  • Ericson - Student
  • Lukman Hakim Lecturer

Abstract

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.

References

[1] Amat, R., Sari, J. Y., & Ningrum, I. P. (2017). Implementasi Metode Local Binary Patterns Untuk Pengenalan Pola Huruf Hiragana Dan Katakana Pada Smartphone. JUTI: Jurnal Ilmiah Teknologi Informasi, 15(2), 152.

[2] Davies, E. R. Computer Vision: Principles, Algorithms, Applications, Learning. In: Computer Vision: Principles, Algorithms, Applications, Learning. 5th ed. USA. Academic Press, 2017: hal. 1–13.

[3] Hakim, M. F. T. (2018). RANCANG BANGUN SISTEM DETEKSI RAMBU – RAMBU LALU LINTAS MENGGUNAKAN JARINGAN SYARAF. Institut Teknologi Sepuluh Nopember.

[4] https://pemrogramanmatlab.com/2017/07/26/pengolahan-citra-digital/, diakses tanggal 6 Oktober 2021.

[5] Imron, M., Perdanawanti, L., Informasi, S., & AMIKOM Purwokerto Jl Letjend Pol Sumarto, S. (2017). Algoritma Decision Tree-J48, K-Nearest, Dan Zero-R Pada Kinerja Akademik. Seminar Nasional Teknologi Informasi, 12–18.
Published
2022-01-19
How to Cite
TANUWIDJAYA, Kevin; -, Ericson; HAKIM, Lukman. KLASIFIKASI RAMBU LALU LINTAS MENGGUNAKAN DECISION TREE J48 DAN LOCAL BINARY PATTERN. JITTER : Jurnal Ilmiah Teknologi dan Komputer, [S.l.], v. 3, n. 1, p. 779-785, jan. 2022. ISSN 2747-1233. Available at: <https://ojs.unud.ac.id/index.php/jitter/article/view/81150>. Date accessed: 23 nov. 2024. doi: https://doi.org/10.24843/JTRTI.2022.v03.i01.p13.

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