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All Journal International Journal of Electrical and Computer Engineering Jurnal Edukasi Elektro Jurnal Teknologi Informasi dan Ilmu Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal CoreIT BAREKENG: Jurnal Ilmu Matematika dan Terapan PRODUCTUM : Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) International Journal of Computing Science and Applied Mathematics J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informasi dan Pendidikan Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat Economics and Digital Business Review NUCLEUS: Jurnal Sains dan Teknologi Jurnal ComunitA Servizio Jurnal Pengabdian Masyarakat Akademisi Economic Reviews Journal JatiRenov: Jurnal Aplikasi Teknologi Rekayasa dan Inovasi JSSIT: Jurnal Sains dan Sains Terapan
Prasetyo, Tegar
Information Technology, Faculty Of Vocational Studies, Institut Teknologi Del
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Journal : International Journal of Electrical and Computer Engineering

 1 
Corn Plant Disease Classification Based on Leaf using Residual Networks-9 Architecture Tegar Arifin Prasetyo; Victor Lambok Desrony; Henny Flora Panjaitan; Romauli Sianipar; Yohanssen Pratama
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2908-2920

Abstract

Classification on corn plants is used to classify leaf of corn plants that are healthy and have diseases consisting of Northern Leaf Blight, Common Rust and Gray Leaf Spot. Convolutional Neural Network (CNN) is one of algorithms from the branch of deep learning that utilizes artificial neural networks to produce accurate results in classifying an image. In this study, ResNet-9 architecture implemented to build the best model CNN for classification corn plant diseases. After that we doing comparisons of epochs have been carried out to obtain the best model, including comparisons of epochs of 5, 25, 55, 75 and 100. After the epoch comparison, the highest accuracy value was obtained in the 100 epoch experiment so that in this study 100 epochs were used in model formation. The number of datasets used is 9145 data which is divided into two, there are training data (80%) and testing data (20%). In this study, three hyperparameter tuning experiments were carried out and the results of hyperparameter tuning experiments where num_workers is 4 and batch_size is 32. This classification obtained an accuracy rate of 99% and the model is implemented into a web interface.
Genetic algorithm to optimization mobility-based dengue mathematical model Tegar Arifin Prasetyo; Roberd Saragih; Dewi Handayani
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4535-4546

Abstract

Implementation of vaccines, mosquito repellents and several Wolbachia schemes have been proposed recently as strategies against dengue. Research showed that the use of vaccine and repellent is highly effective when implemented to individuals who are in area with high transmission rates, while the use of Wolbachia bacteria is strongly effective when implemented in area with low transmission rates. This research is to show a three-strategy combination to cope with the dengue using mathematical model. In dengue mathematical model construction, several parameters are not yet known, therefore a genetic algorithm method was used to estimate dengue model parameters. Numerical simulation results showed that the combination of three strategies were able to reduce the number of infected humans. The dynamic of the human population with the combination of three strategies on average was able to reduce the infected human population by 45.2% in immobility aspect. Furthermore, the mobility aspect in dengue model was presented by reviewing two areas; Yogyakarta and Semarang in Indonesia. The numerical solutions showed that the trend graph was almost similar between the two areas. With the maximum effort given, the combination control values decreased slowly until the 100th day.
Optimizing parameter selection in bidirectional encoder portrayal for transformers algorithm using particle swarm optimization for artificial intelligence generate essay detection Prasetyo, Tegar Arifin; Chandra, Rudy; Siagian, Wesly Mailander; Siregar, Horas Marolop Amsal; Siahaan, Samuel Jefri Saputra
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5543-5554

Abstract

This research proposes a novel method for detecting artificial intelligence (AI)-generated essays by integrating the bidirectional encoder representations from transformers (BERT) model with particle swarm optimization (PSO). Unlike traditional approaches that rely on manual hyperparameter tuning, this study introduces a systematic optimization technique using PSO to improve BERT’s performance in identifying AI-generated content. The key problem addressed is the lack of effective, real-time detection systems that preserve academic integrity amidst rapid AI advancements. This optimization enhances the model’s detection accuracy and operational efficiency. The research dataset consisted of 46,246 essays, which, after data cleaning, were refined to 44,868. The model was then tested on 9,250 essays. Initial evaluations showed BERT's accuracy ranging from 83% to 94%. After being optimized with PSO, the model achieved an accuracy of 98%, an F1-score of 98.31%, precision of 97.75%, and recall of 98.87%. The model was deployed using a FastAPI-based web interface, enabling real-time detection and providing users with an efficient way to quickly verify text authenticity. This research contributes a scalable, automated solution for AI-generated text detection and offers promising implications for its application in various academic and digital content verification contexts.
Co-Authors Abi Burhan Adha, Ufairi Africano, Fernando Agustin, Ririn Dita Aji Nugraha, Yoga Akbar, M. Jofandio Amri Yahya, Muhammad Anastasia Marsada Uli Simamora Andree Panjaitan Aprianda, Ridho Ardian, Rizki Asido Saragih Aulia Akhmad BillY Dewantara Christian Benedict Lumbantoruan Dame Sisri Haryati Katarina Rumapea Desiana, Lidia Dewi Handayani Ebtaria Nadeak, Ebtaria Edi Kurniawan Eka Putri Manurung, Nancy Elmi Rahmawati, Elmi Emy Sonia Sinambela Ester Saulina Hutabarat Evan Richardo Sianipar Evelina Evelina Fauziah, Putri Khafifah Fernandez, Melanie Frengki Simatupang Fritz Marpaung Gemala Cahya Goklas Henry Agus Panjaitan Hafizah, Nanda Nur Hamzah, Muhammad Luthfi Henny Flora Panjaitan Henry Agus Panjaitan , Goklas Henry Agus Panjaitan, Goklas Herbeth Augustinus Napitupulu Hermialingga, Septi Iammillah, Azmiyatul Ilhami, Ilhami Italiano Wowiling, Gerry Joshua Pratama Silitonga Juan Carlos Munthe Juli Yanti Damanik Juniasari, Juniasari Lawy Xenna Lestari, Leni Ayu Lilis Marito Pardosi Lumban Gaol, Tiurma Lumbangaol, Heni Ernita Manurung, Nancy Eka Putri Matthew Alfredo Mei Pane Muhammad Fikri Muhammad Ilham Maulana Muhammad Rizki Mula Timbul Sigiro, Marojahan N. Nazaruddin Najah, Nabila Safinatun Nathan Fernando Lumban Tobing Nico Felix Sipahutar Nugraha, Yoga Aji Panca Rahmat Siagian, Iqbal Pangaribuan, Maria Partogi Pardede, Immanuel Pasaribu, Monalisa Poibe Leny Naomi Pratami, Viekhen Irza Putri Manurung, Nancy Eka Risky Saputra Siahaan Roberd Saragih Romauli Sianipar Rudy Chandra Rudy Chandra Safitri, Nita Octaria Samuel Sibuea Saodin, Saodin Sarbaini Sarbaini Sarbaini Sarbaini Sari Utami, Aldila SIAGIAN, WESLY MAILANDER Siahaan, Samuel Jefri Saputra Siahaan, Veny Sianipar, Johan Immanuel Silaen, Willy Cristover Silvia Agustin Siregar, Horas Marolop Amsal Suandika Napitupulu Tahan HJ Sihombing Tanjung, Muhammad Al Chapis Abdilla Tessalonika Siahaan Timothy Timothy Tiurma Lumban Gaol Togu Novriansyah Turnip Trito Exaudi Manik Umam, Muhammad Isnaini Hadiyul Victor Lambok Desrony Wardani, Yoshinta Kusuma Wesly Mailander Siagian Yahya, Muhammad Amri Yohana Sihombing Yohanssen Pratama