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All Journal Majalah Ilmiah Sultan Agung TEKNIK INFORMATIKA Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil Pondasi JITEK (Jurnal Ilmiah Teknosains) Innovative: Journal Of Social Science Research
Abdul Rochim
Universitas Islam Sultan Agung
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Mechanical Engineering Physics Public Health Social Sciences Transportation Veterinary Other

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Journal : TEKNIK INFORMATIKA

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IDENTIFIKASI SERAT BAMBU MENGGUNAKAN EKSTRAKSI CIRI STATISTIK ORDE 2 (GLCM) DAN PENGUKURAN JARAK K-NN Khoiriya Latifah; Abdul Rochim; Bambang Supriyadi
JURNAL TEKNIK INFORMATIKA Vol 12, No 2 (2019): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.185 KB) | DOI: 10.15408/jti.v12i2.8946

Abstract

Indonesia is a large bamboo producer. Many benefits can be taken from bamboo trees, among others, as an alternative material for environmentally friendly construction, handicraft, and even become a safe material for use. Based on the property of its mechanical strength, bamboo has high tensile strength and fiber content, including fiber length, inter-fiber adhesive, namely lignin and the higher diameter of bamboo fiber, causing bamboo stems to become stronger and stiffer so that bamboo quality is getting better. One objective is to use a texture analysis of statistical features extraction of digital image processing. Feature extraction is a process to get the characteristics of visual perception. Texture information can be used to distinguish the surface properties of objects in images that are related to coarse and fine. This research uses a second-order statistical calculation of Gray Level Co-occurrence Matrices (GLCM) by measuring contrast, energy, homogeneity, and correlation levels to determine roughness from bamboo image textures that have irregular patterns. The second method is to use similarity measurements with the K-NN method in which in this study K = 3 with testing images of 28 images obtained an accuracy of 0.8, precission of 0, 8 and f-measurement of 0.9.
Co-Authors Ardian Fachrurrozi Bambang Supriyadi Henny Pratiwi Adi Khoiriya Latifah, Khoiriya Muhammad Abdul Khalim Mulyadi Mulyadi Pratikso Pratikso Rachmat Mudiyono Sahal Priyono Putra Sholahudin, Farhan Sumirin Sumirin