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Journal : Jurnal Teknik Informatika (JUTIF)

APPLICATION OF VGG16 ARCHITECTURE IN WOOD TYPE CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK Afiah, Nurul Anggun; Syahrullah, Syahrullah; Ardiansyah, Rizka; Laila, Rahmah; Pohontu, Rinianty
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.3874

Abstract

Wood is an important natural resource in construction and the furniture industry, with various types possessing unique characteristics. The selection of wood types is often done manually, which is prone to errors that can negatively impact the working process, product quality, and the sustainability of the forests that source the wood. Therefore, this research aims to improve classification accuracy through the application of technology. This study utilizes Convolutional Neural Network (CNN) with the VGG16 architecture to process images in analyzing the visual characteristics of wood, with the goal of building a model capable of classifying wood types based on images. The dataset used consists of 1,584 samples of wood images sourced from Kaggle. Four models were tested with variations in the training and validation data splits, as well as the use of Adam and Adamax optimizers, over 100 epochs. Model 1 achieved a training accuracy of 96.68% and a testing accuracy of 98.10%. Model 2, with a training accuracy of 99.47% and a testing accuracy of 98.41%, showed the best performance. Models 3 and 4 also yielded testing accuracies of 97.46% and 97.78%, respectively. The results of this study indicate that the application of CNN with the VGG16 architecture can enhance the effectiveness of wood type classification and contribute to more accurate and efficient wood selection practices.
Co-Authors A Wahab Jufri Absor, Sholihul Afiah, Nurul Anggun Al Hakim, Roby Maulana Anggreni, Dwi Shinta Anita Ahmad Kasim Anita, Ayu Anwar, Asriani Azkia, St. Aulia Billyardi Ramdhan Bogheiry, Ali Chairunnisa Ar. Lamasitudju Chirzun, Ahmad Damayanti, Sherli Darojah, Murtafiatun Deny Wiria Nugraha Dessy Santi Diana Wahyuni Sulasti Dwi Shinta Angreni Dwiyanto, Andika Fahrudda, Ansarul Fajriyah, Nurul Faldiansyah, Faldiansyah Firhan Nurfaizi Hajra Rasmita Ngemba Haniifah, Ulaa Hartamto, Offia Melda Permata Imam Abdullah , Ahmad Imam Wahyudi Indrawan, Imam Wahyudi Imas Hasdianti Jamil, Ahmad Mochtar Jonathan Wongkar, Noel Marcell Joned Bangkit Wahyu Laksono Jujun Ratnasari Kasaedja, Tafania Natalia Laala, Jonathan Zebina Lamadjido, Moh. Raihan Dirga Putra M Thaha, M M Zakaria Meyssa Dwi Miftah Miftah Miftah, Miftah Mohammad Yazdi Pusadan Muhammad Anas Muhammad Jindan Mundakir Ningsih, Alief Surya Nouval Trezandy Lapatta Nugroho, Yudhistiro Andri Nurholisoh, Siti Nursalim, Moh. Agung Nursiana Zasqia, Andi Nirina Pratama, Moh. Asry Eka Pratiwi, Dian Asri Puspita, Eka Ari Qothrunnada, Widya Rahmasena, Naomi Rasmita Ngemba, Hajra Rifai, Muhammad Fajar Rima Ahadiah Rini Septiani Rinianty, Rinianty Risaldi Pata’Dungan, Adi Rita Arlitia Rizka Ardiansyah Rizki Hegia Sampurna Rosmala Nur Ruddy Indra Frahasta Rumampuk, Viola Gracella Ryfial Azhar, Ryfial Saleh, Muhammad Taufik Salhudin, Salhudin Selpi Susilawati Septiano Anggun Pratama Setiono Setiono Silvi Husnaini Siti Jamilah Siti Khodijah Parinduri Sri Purnawati SRI RAHAYU Sudharsono, Muhamad Suswojo, Heru Syahrullah Syahrullah Syahrullah Syaiful Hendra Teti Damayanti Thaha, M. Thaha TITIN SUNARYATI Tuah Nur Ulfa Fauzi Vira Safitri Aulia Widyati, Made Ayu Sri Wilda Waliam Wirdayanti Wiska Hera Yudhaswana, Yuri Yuri Yudhaswana Joefrie Yusuf Anshori