Article Per Year (5 Year)
p-Index From 2019 - 2024
2.517
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering 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 International Journal of Computing Science and Applied Mathematics Jurnal Teknologi Informasi dan Pendidikan Indonesian Journal of Electrical Engineering and Computer Science NUCLEUS: Jurnal Sains dan Teknologi Jurnal ComunitA Servizio
Prasetyo, Tegar Arifin
Information Technology, Faculty Of Vocational Studies, Institut Teknologi Del
Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Transportation

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
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.
Co-Authors Andree Panjaitan Asido Saragih Christian Benedict Lumbantoruan Dame Sisri Haryati Katarina Rumapea Dewi Handayani Ester Saulina Hutabarat Evan Richardo Sianipar Fritz Marpaung Goklas Henry Agus Panjaitan Heni Ernita Lumbangaol Henny Flora Panjaitan Herbeth Augustinus Napitupulu Johan Immanuel Sianipar Joshua Pratama Silitonga Juan Carlos Munthe Juli Yanti Damanik Lawy Xenna Lilis Marito Pardosi Matthew Alfredo Mei Pane Muhammad Isnaini Hadiyul Umam Muhammad Luthfi Hamzah Muhammad Rizki Nathan Fernando Lumban Tobing Nazaruddin Nazaruddin Nico Felix Sipahutar Pasaribu, Monalisa Poibe Leny Naomi Risky Saputra Siahaan Roberd Saragih Romauli Sianipar Rudy Chandra Rudy Chandra Samuel Sibuea Sarbaini Sarbaini SIAGIAN, WESLY MAILANDER Tahan HJ Sihombing Tahan HJ Sihombing Tessalonika Siahaan Timothy Timothy Tiurma Lumban Gaol Togu Novriansyah Turnip Trito Exaudi Manik Veny Siahaan Victor Lambok Desrony Yohana Sihombing Yohanssen Pratama