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Journal : Jurnal Rekayasa elektrika

Wood Species Identification Based on Gray Level Co-Occurrence Matrix (GLCM) Features on Macroscopic Images Ilham Ramadhan, Muhammad Ghiffaari; Sugiarto, Bambang; Dwi Mulya, Okta; Septian Chairulsyah, Defti; Syahrizal, Adyanto; Gunawan, Gunawan; Haviani Laluma, Riffa; Nuraini Sukmana, Rini; Wiharko, Teguh
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.41078

Abstract

Wood is an incredibly valuable resource, particularly for everyday living. To fully harness the advantages of wood, it must focus on two key considerations. Firstly, it is imperative to consistently utilize wood sourced from sustainably managed forests. Secondly, we must explore techniques that maximize the utilization of every part of the tree. One technique for meeting these considerations is to create a wood identification system. This system can be used for quickly inspecting wood species. In wood identification, it is essential to consider specific characteristics and physical properties of wood. Manual identification will depend on the examination of wood anatomists eye and will require a significant amount of time. In accordance with these situations, a computer vision-based system can address this condition. Therefore, feature extraction is necessary to extract the features of wood characteristics from the wood image. This research aims to propose a method for wood species identification based on Gray Level Co-occurrence Matrix (GLCM) features to extract important information about wood characteristics from macroscopic wood images. For the classifier, the Random Forest algorithm is proposed for the identification of the machine learning model. Five wood species images will be used in this research, with each wood sample being presented as a macroscopic image. The total dataset used was 750 images, with each wood species having 150 images. The result showed that the Model C (90/10) training data ratio demonstrates good performance in classifying wood species from the macroscopic images. The model achieved a peak accuracy of 0.81 and correctly predicted all test images. This study indicates that the Random Forest model can be an effective classifier for wood species identification.
Co-Authors Achmad, Zubaidi Adawiah, Lulu Robiatul Ade Kurniawan Agama, Askar Adika Ahmad Hasyim Amaria Amaria Anggarani, Riesta Ardiyani, Anita Nur Auzani, Ahmad Syihan Bagusputra, Argan Imam Bustanul Arifin Christy Atika Sari Dendi, Dede Dewanata, Rachman Pandu Dewi, Cicilia Tri Marantika Dhiani Dyahjatmayanti Dwi Mulya, Okta Endah Wahyurini, Endah ENDANG SUSANTINI Erwin, Iwan Muhammad Fatchurohman, Dedi Fatman, Yenni Frans Setiawan, Frans G.M. Lucki Junursyah, G.M. Lucki Gunawan Gunawan Gunawansyah Gunawansyah, Gunawansyah Handayani, Sri Hanifuddin, M Hapsari, Nani Sarah Hasibuan, Juana Hizkia Haviani Laluma, Riffa Hendranto, Rahadian Yogi Hendrawan, Rizqi Ainur Hendro Widjanarko Hermawan, Angga Dimas Heru Sigit Purwanto Ikhsan, Akhmad Fauzi Ilham Ramadhan, Muhammad Ghiffaari Indra Sakti Indyo Pratomo Iqbal, Fahmi Mohamad Irfandi, Fauzan Isnaini Nur Azizah, Isnaini Ivany Sarief, Ivany Kusuma, Heri Septya Lucki Junursyah, G.M Mariska Aulia Putri, Indah Merdeka Putri, Wulandari Pancadasa Mokhtar, Mokhtar Muchlis Muchlis Nathaniel, Adriel Ningsih, Ristati Nugraha, Muhammad Fauzi Nur, Salsabila Nuraini Sukmana, Rini Nurfitriani, Nisa Nurholis Majid, Nurholis Nyamiati, Retno Dwi PRABOWO Prakarsa, Esa Praromadani, Zulimatul Safa'ah Prasetya, Angga Proklamagita, Angela Merici Herdyana Putri, Sari Rahmawati Ramadhan, Zulqy Fazrie Ramdhani, Muhamad Deris Riffa Haviani Laluma Rirung, Yustin Risnandar, Risnandar Rizqon Fajar Rokhis, Tria Ainur Rukmana, Ade Samidi Samidi, Samidi Santosa Utomo, Humam Saputra, Krisna Arga Septian Chairulsyah, Defti Setyawan, Tri Aji Sifa Nurpadillah Sri Poedjiastoeti Sulistyowati, RR Endang Suranto Suranto SUYONO Suyono Suyono Syahrizal, Adyanto Syech Ahmad, Mochamad Taufik Ali Taufik Suryantoro, Taufik Taufiqurrahman, Muhammad Faja Tiara, Dinda Raihan Tunjung Wahyu Widayati Tuqa, Eka Tina Nur Ula Ummi Kalsum Wellia Shinta Sari Wibowo, Cahyo Setyo Widayati, Tunjung Wahyu Wiharko, Teguh Wiharso, Tri Arif Wirawan, Kristuaji Andre Wulandari, Amelia Puspita Yuliana, Siska Yulianto Sulistyo Nugroho