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All Journal Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Rekayasa elektrika
Maya Fitria
Department Of Electrical And Computer Engineering, Universitas Syiah Kuala. Jl. Tgk. Syech Abdur Rauf No. 7 Kopelma Darussalam, Banda Aceh 23111|Universitas Syiah Kuala
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Implementing a non-local means method to CTA data of aortic dissection Maya Fitria; Cosmin Adrian Morariu; Josef Pauli; Ramzi Adriman
Jurnal Teknologi dan Sistem Komputer Volume 9, Issue 3, Year 2021 (July 2021)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2021.14125

Abstract

It is necessary to conserve important information, like edges, details, and textures, in CT aortic dissection images, as this helps the radiologist examine and diagnose the disease. Hence, a less noisy image is required to support medical experts in performing better diagnoses. In this work, the non-local means (NLM) method is conducted to minimize the noise in CT images of aortic dissection patients as a preprocessing step to produce accurate aortic segmentation results. The method is implemented in an existing segmentation system using six different kernel functions, and the evaluation is done by assessing DSC, precision, and recall of segmentation results. Furthermore, the visual quality of denoised images is also taken into account to be determined. Besides, a comparative analysis between NLM and other denoising methods is done in this experiment. The results showed that NLM yields encouraging segmentation results, even though the visualization of denoised images is unacceptable. Applying the NLM algorithm with the flat function provides the highest DSC, precision, and recall values of 0.937101, 0.954835, and 0.920517 consecutively.
Sybil Attack Prediction on Vehicle Network Using Deep Learning Zulfahmi Helmi; Ramzi Adriman; Teuku Yuliar Arif; Hubbul Walidainy; Maya Fitria
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 3 (2022): Juni 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (434.315 KB) | DOI: 10.29207/resti.v6i3.4089

Abstract

Vehicular Ad Hoc Network (VANET) or vehicle network is a technology developed for autonomous vehicles in Intelligent Transportation Systems (ITS). The communication system of VANET is using a wireless network that is potentially being attacked. The Sybil attack is one of the attacks that occur by broadcasting spurious information to the nodes in the network and could cause a crippled network. The Sybil strikes the network by camouflaging themselves as a node and providing false information to nearby nodes. This study is conducted to predict the Sybil attack by analyzing the attack pattern using a deep learning algorithm. The variables exerted in this research are time, location, and traffic density. By implementing a deep learning algorithm enacting the Sybil attack pattern and combining several variables, such as time, position, and traffic density, it reaches 94% of detected Sybil attacks.
Heart Attack Notification and Monitoring System Using Internet of Things Maya Fitria; Ramzi Adriman; Irham Muhammaddin Batubara; Akhyar Bintang
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4509

Abstract

People are frequently shocked when someone passes away suddenly without any prior symptoms. One of the contributing factors is a heart attack. This condition might occur anywhere and at any time. A sudden heart attack can be highly perilous for a person who is alone, without family members or friends because the family cannot be informed of the victim's condition or their location. Therefore, it is vital to raise awareness of heart attacks. With the support of the Internet of Things, this study aims to develop a wearable device that people may use to monitor their heart health and connect with hospitals to get alerts in case of a heart attack. This system also provides family members with access to a web-based patient monitoring tool. The heart beat is considered as the parameter in developing this system. There are three types of evaluation which are conducted in this study, namely: 1) Sub-system evaluation; 2) Black-box testing; and 3) Integrating system testing. The three evaluation results show that all assembled hardware components are work properly and the system effectively satisfies the objectives of monitoring, buzzer activation, hospital and patient family notification, and so forth, with 1.96% average sensor error, which is still considerably acceptable.
A Usability Analysis of QODE: Qurbani Web Application System Dalila Husna Yunardi; Maya Fitria; Rahmad Dawood; Teuku M. Syahril Nur Alamsyah
Jurnal Rekayasa Elektrika Vol 18, No 3 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v18i3.27227

Abstract

Qurbani is an Islamic ritual animal sacrifice that is carried out during Eid-Adha; one of the two major Muslim holidays. In Indonesia, every village normally has one mosque that takes charge of organizing any related Qurbani activities, from collecting money, creating slaughter schedule, to distributing the meat for the recipients. The current management of these activities is done manually and by hand, which can potentially have errors. Therefore, this research aims to develop and evaluate the usability of a web-based application that will in part take care of Qurbani-related activities. This application is designed and developed using the Scrum methodology. The application as successfully developed and its functionalities are as expected based on design. The application was then evaluated using System Usability Scale (SUS) with 10 respondents. The application obtained the average score of 91.25 which falls into A or excellent category.
Co-Authors Adriman, Ramzi Akhyar Bintang Ali Djamhuri Cosmin Adrian Morariu Dalila Husna Yunardi Hubbul Walidainy Irham Muhammaddin Batubara Josef Pauli Rahmad Dawood Teuku M. Syahril Nur Alamsyah Teuku Yuliar Arif Zulfahmi Helmi