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All Journal Jurnal Sarjana Teknik Informatika International Journal of Artificial Intelligence Research KACANEGARA Jurnal Pengabdian pada Masyarakat Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics Signal and Image Processing Letters Science in Information Technology Letters Signal and Image Processing Letters
Adhi Prahara, Adhi
Universitas Ahmad Dahlan
Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Neuroscience

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Journal : Mobile and Forensics

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Classification of Tiles using Convolutional Neural Network Ramadayanti, Susanti Aulia; Prahara, Adhi
Mobile and Forensics Vol. 3 No. 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v3i2.5643

Abstract

Tiles are one of the building materials with various types that can make a residence more elegant, attractive, and colorful. However, not all people know about the types of tiles and their advantages. Therefore, a Convolutional Neural Networks (CNN) based method is proposed to make it easier for people to accurately recognize tiles based on their types and know their advantages. The purpose of this paper is to classify the types of tiles using CNN which is based on VGG16 model. The proposed method classifies tiles into 6 classes, namely granite, limestone, marble, motifs, mosaics, and terrazzo. This research uses 186 training data, 96 validation data and 60 test data with image resolution of 224x224. Based on the experiments, the training process produces 100% of training accuracy and 94% of validation accuracy. The testing process achieves 98.33% accuracy which can be concluded that the proposed CNN model able to classify the types of tiles well.
Motion Capture Technique with Enhancement Filters for Humanoid Model Movement Animation Habibillah, Ahmad Yasin; Prahara, Adhi; Murinto, Murinto
Mobile and Forensics Vol. 5 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v5i1.6534

Abstract

The definition of 3D animation is a representation of objects that are made into animation using characters or objects to look more alive and real. Making 3D animation itself requires a long process and a large amount of funding. This is because most 3D animated films still use key-framing technology which causes the process to make an animation to take a lot of steps. In this research, a motion capture technique with an enhancement filter is proposed to make humanoid movement animation using Kinect 2.0. The method consists of several steps such as recording every skeleton joint of human movements using a Kinect sensor, filtering the movements to minimize the shakiness and jitter from Kinect data, mapping skeleton data to the bones of a rigged humanoid model, and recording each movement to make animation. The final result is in the form of a 3D animation of modern dance movements. The method is tested by measuring the similarity between the 3D humanoid model and the user movement. From the 10 animations of modern dance generated by the method and performed by the user, a questionnaire to measure the MRI and MSE value is distributed and the result achieves 4.27 on a scale of 5 for the averaged MRI score and 0.0539 for the MSE score. The MSE value is less than 5% which means the system is categorized as acceptable.
Co-Authors A.A. Ketut Agung Cahyawan W Abdillah, Aldi Khoirul Ahmad Azhari Alqorni, Wais ALYA MASITHA Anggisa, Ahmad Bramdimas Anwar, Kaspul Arif Budi Setiawan Banjaransari, Muhammad Fatkhannudin, Muhammad Noor Fatkhannudin, Muhammad Noor Habibillah, Ahmad Yasin Herman Yuliansyah, Herman Indikawati, Fitri Indra Jefree Fahana Laelatul Azizah, Laelatul Munif, Rihwan Murinto Murinto Pramesti, Mara Indar Ramadayanti, Susanti Aulia Rani, Siti Sofia Romadhoni, Ilham Fauzi Son Ali Akbar