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All Journal Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Alqaroni Alqaroni
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Computer Science & IT Electrical & Electronics Engineering

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Grey Level Co-Occurrence Matrix (GLCM) & Hybrid Klasifikasi untuk Mendeteksi Kerusakan Jalan Aspal Ika Maylani; Virginia Wahyu Ambarwati; Bismar Wasykuru; Alqaroni Alqaroni; Firnanda Tri Buana Kusuma Wati
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2023: SNESTIK III
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2023.4219

Abstract

The importance of detecting damage to the asphalt road surface is to minimize the occurrence of accidents caused by uneven road surfaces. Image extraction can be used to detect road surface damage. GLCM is a statistical method in which statistical calculations use the distribution of gray degrees (histograms) by measuring the level of contrast, granularity, and roughness of an area from the neighboring pixels in the image. The classification process uses a hybrid classification, which combines the SVM method with kernel changes and KNN with changes in k=3, 4, 5, 7 and 9 tracts.
Co-Authors Bismar Wasykuru Firnanda Tri Buana Kusuma Wati Ika Maylani Virginia Wahyu Ambarwati