Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Akhyar Bintang
Universitas Syiah Kuala
Computer Science & IT Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
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.
Improved Classification of Handwritten Jawi Script Based on Main Part of Script Body Safrizal Razali; Fitri Arnia; Rusdha Muharrar; Kahlil Muchtar; Akhyar Bintang
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4600

Abstract

Since the entry of Islam, many ancient relics in the archipelago were written using Jawi script. Due to human or natural factors, these ancient relics will be damaged or destroyed. To avoid the loss of this ancient heritage data, the data must be stored in digital documents. In order to convert digital documents into machine-readable text format, the use of Optical Character Recognition (OCR) technology is inevitable. In this research, OCR technology is implemented on isolated Jawi scripts. Freeman Chain Code (FCC) is used to extract the isolated Jawi script features. Subsequently, the FCC feature is fed into Support Vector Machine (SVM) in order to classify the character. The decision rule classification is applied to the class of SVM classification in the Jawi script form. The results of the SVM classification into 19 classes reached 81.58%, while the results for merging into 15 classes produced better results with the accuracy 84.21%. Feature extraction of dot location is divided into the top, middle, and bottom. Feature extraction of the number of dotss is done by counting the number of dots, while feature extraction of the presence of holes is carried out by detecting the presence of holes in the characters. These features are applied to the class of results from SVM classification with decision-making rules. The percentage of success in applying the decision rules to the results of the classification of incorporation into 15 classes by SVM reached 92.86%. Further research will be conducted to determine the effect of the feature of the location of the dot and the number of dots on the shape of the main part of the character.
Co-Authors Adriman, Ramzi Fitri Arnia Irham Muhammaddin Batubara Kahlil Muchtar Maya Fitria Rusdha Muharrar Safrizal Razali