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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Rekayasa Mesin Jurnal Rekayasa Mesin JOIV : International Journal on Informatics Visualization JURNAL CRANKSHAFT Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Abdi Masyarakat Indonesia Eksergi: Jurnal Teknik Energi Jurnal Hilirisasi Technology kepada Masyarakat (SITECHMAS) Journal of Mechanical Engineering and Applied Technology Jurnal Polimesin Widya Teknik
Putri, Farika Tono
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Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences

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Journal : JOIV : International Journal on Informatics Visualization

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Artificial Neural Network Accuracy Optimization Using Transfer Function Methods on Various Human Gait Walking Environments Indrawati, Ragil Tri; Putri, Farika Tono; Safriana, Eni; Isti Nugroho, Wahyu; Prawibowo, Hartanto; Ariyanto, Mochammad
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2159

Abstract

A bionic leg with ergonomic functionality can increase the user’s independence. However, an ergonomic bionic leg can be challenged to be developed. One of its challenges is related to functionality, where the bionic leg motor can be rugged to adapt to the user. One of the solutions for the bionic leg challenge is the application of a motor driver controlled by the user’s muscle signal. EMG signal can be utilized as the user’s signal source. The EMG signal is then fed back into the motor device. EMG signals obtained during a natural walking environment can result in smooth and natural movement. This study classifies EMG signals into 8 classes: a controlled walking environment (treadmill walking with various speeds) and a natural walking environment (ground walking, upstairs and downstairs walking). This research aims to optimize the ANN method using transfer function variations. The best method will be used to train EMG-driven motors for future studies related to bionic legs. The best ANN parameter in this research using Levenberg-Marquardt backpropagation as a training algorithm with transfer function pairing of the exponential function: Hyperbolic tangent sigmoid transfer function and SoftMax transfer function with 98.8% accuracy and 0.036 MSE value. The best method from the experiment and ANN classification can be used as a training method for a bionic leg in future research.
Determining the Rice Seeds Quality Using Convolutional Neural Network Hidayat, Sidiq Syamsul; Rahmawati, Dwi; Prabowo, Muhamad Cahyo Ardi; Triyono, Liliek; Putri, Farika Tono
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1175

Abstract

Seed inspection is crucial for plant nurseries and farmers as it ensures seed quality when growing seedlings. It is traditionally accomplished by expert inspectors filtering samples manually, but there are some challenges, such as cost, accuracy, and large numbers. Speed and accuracy were the main conditions for increasing agricultural productivity. Machine learning is a sub-science of Artificial Intelligence that can be applied in research on the classification of rice seed quality. The pipeline of a machine learning system is dataset collection, training, validation, and testing. Model making begins with taking data on the characteristics of rice seeds based on physical parameters in the form of seed shape and color. The dataset used is two thousand images divided into two categories, namely superior seeds and non-superior seeds. Training and Validation was conducted using the Convolutional Neural Network (CNN) algorithm with the concept of cross-validation on Google Collaboratory notebooks. The ratio split of train data and validation data in modeling from a dataset is 80:20. The result of the model formed is a model with the development of a Deep Convolutional Neural Network (Deep CNN) that can classify the digital image data of rice seeds from the results of data calls uploaded into the system. The results of the experiment conducted on 30 test data can be analyzed so that the system can classify superior and non-superior seeds with a precision value of 93% and a recall of 95%.
Co-Authors A Fauzi, Abdul Syukur Agus Slamet Ahmad Jalaludin, Ahmad Alfauzi, Abdul Syukur Amarta, Rona Zaqqi Andreyanto W, Mirda Anggit, Timotius Anis Roihatin Atmojo, Slamet Priyo Ayu S, Friska Balqis Balqis Bayu Setyo Nugroho, Bayu Setyo Bono Bono Budhi Prasetyo Carli Carli DWI RAHMAWATI Eko Saputra Eko Saputra Fathoni, Achmad Luthfian Firmansyah, Erik Fuad Hilmy Gutomo, Gutomo Huda, Evan Hardi Nurul Huda, Mohammad Ragil Nur Ikhsan, Ivan Hardi Nurul Indra, Ragil Tri Indrawati, Ragil Tri Ismail, Rima Ruktiari Isti Nugroho, Wahyu Kabir, Noer Ni'mat Syamsu Kadavi, Fadhil Kadavi, Fadhil Muhammad Khoryanton, Ampala La Ode Ichlas Syahrullah Yunus Luthfiansyah, Galih Mara, Muhlasah Novitasari Margana Margana Mochammad Ariyanto Muryanto Nailul Ulum, Muhammad Showi Nashrullah, Miftah Nugroho , Bayu Setyo Nugroho, Agung Nugroho, Irvandianto Padang Yanuar Pasmanasari, Elta Diah Prabowo, Muhamad Cahyo Ardi Prasetyo, Sandif Pratama, Fandy Indra Pratama, Galang Dimas Prawibowo, Hartanto Purnomo, Adhy Purwati, Wiwik R., Rizkha Ajeng Rachman, Fathur Rafsanjanu, Swastika Pascal Rifky Ismail Rochmatika, Rizkha Ajeng Rohmatika, Rizka Ajeng Safirana, Eni Safriana, Eni Sahid Sahid Sai'in, Ali Satito, Aryo Setiyawan, Trio Sidiq Syamsul Hidayat, Sidiq Syamsul Sitepu, Rasional Slamet Priyoatmojo, Slamet Solly Aryza Sri Hastuti Sri Wahyuni Sriharmanto, Sriharmanto Supandi Supriyo Supriyo Supriyo Timotius Anggit Kristiawan Tristidjanto, Hery Triyono, Liliek Wahyu Isti Nugroho Xander Salahudin Yusuf Dewantoro Herlambang Zaenal Abidin