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All Journal JSAI (Journal Scientific and Applied Informatics) International Journal of Robotics and Control Systems
Iis Setiawan Mangkunegara
Universitas Harapan Bangsa
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Evaluation of Stochastic Gradient Descent Optimizer on U-Net Architecture for Brain Tumor Segmentation Purwono Purwono; Iis Setiawan Mangkunegara
International Journal of Robotics and Control Systems Vol 3, No 3 (2023)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v3i3.1104

Abstract

A brain tumor is a type of disease that is quite dangerous in the world. This disease is one of the main causes of human death and has a high risk of recurrence. There are several types of brain tumor locations such as edema, necrosis to elevation. Segmenting the location of this disease is important to do to support faster recovery efforts. The Convolutional Neural Network (CNN) algorithm, which is part of the deep learning method, can be an alternative to this segmentation effort. The U-Net architecture is part of the CNN algorithm which specifically works on medical image segmentation. This study experimented to build a special U-Net architecture for medical image segmentation that had been optimized with SGD. The data used is BraTS2020O which contains a collection of MRI data. This optimization aims to improve the performance of the U-net architecture for segmenting brain tumor images. The results of the study show that the SGD optimization carried out has succeeded in providing better performance than previous studies. This can be seen from the performance value obtained at 0.9879. This accuracy value indicates an increase in accuracy from previous studies. High accuracy indicates that the SGD-optimized model has good segmentation prediction performance.
Implementasi Arduino Iot Cloud: Potensiometer Sebagai Pengatur Intensitas Cahaya LED Iis Setiawan Mangkunegara; Arif Setia Sandi Ariyanto; Deny Nugroho Triwibowo
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 1 (2024): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i1.6083

Abstract

Development of the Internet of Things in this modern technological era plays a significant role in aiding and simplifying tasks across various industrial sectors. One of the open-source electronic devices, such as Arduino, also advances a platform specifically designed for Internet of Things projects called the Arduino IoT Cloud. In this discussion, the author implements the usage of Arduino IoT Cloud by experimenting with a potentiometer to regulate the intensity or brightness of light on an LED through the Wi-Fi module NodeMCU based on ESP8266. The results of this implementation indicate that Arduino IoT Cloud can be operated to receive analog data from the potentiometer and exhibits stable performance in both receiving and reading data from it. These results are expected to serve as a reference for the development of Internet of Things technology by leveraging Arduino IoT Cloud and potentiometers
Co-Authors Arif Setia Sandi A. Deny Nugroho Triwibowo Purwono, Purwono