cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Risanuri Hidayat
Contact Email
ijitee.ft@ugm.ac.id
Phone
+62274 552305
Journal Mail Official
ijitee.ft@ugm.ac.id
Editorial Address
https://jurnal.ugm.ac.id/ijitee/about/contact
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
IJITEE (International Journal of Information Technology and Electrical Engineering)
Published by Universitas Gadjah Mada
ISSN : -     EISSN : 25500554     DOI : https://doi.org/10.22146/ijitee.48545
Core Subject : Engineering,
Electrical & Electronics Engineering
IJITEE (International Journal of Information Technology and Electrical Engineering), with registered number ISSN 2550-0554 (Online), is a peer-reviewed journal published four times a year (March, June, September, December) by Department of Electrical engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada. IJITEE (International Journal of Information Technology and Electrical Engineering) invites manuscripts in the various topics include, but not limited to, Information Technology, Power Systems, Digital Signal Processing, Communication Systems
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 93 Documents
 6   7   8   9   10 
SMIMO Radar: MIMO Radar with Subarray Elements of Phased-Array Antenna Syahfrizal Tahcfulloh
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 2 (2021): June 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.58593

Abstract

Unlike Phased-MIMO Radar (PMIMO) which employs overlapping equal subarrays (OES) only on the transmit (Tx), Subarray-MIMO (SMIMO) radar utilizes the combination of subarrays, both in the transmit (Tx) and receive (Rx). SMIMO radar is MIMO radar with subarray elements acting as Phased-Array (PA). It simultaneously combines the primary advantages of PA and the MIMO radar; they are high directional gain and high diversity gain, respectively. High directional gain is beneficial to improve the range target, while high diversity gain is beneficial to improve the number of target detection. The use of the subarray methods in the Tx-Rx array could be configured such as in verlapping subarray (OS), non-overlapping subarray (NOS), equal subarray (ES), unequal subarray (US), and/or the combination of all configurations. Various configurations in Tr-Rx would determine the performance of radar, such as the number of virtual arrays, the maximum number of target detections, the detection accuracies, and the angular resolutions along with its effectivity compared to PA, MIMO, and Phased-MIMO radar. Numerical results and simulation showed that SMIMO provided higher flexibility than other radars by configuring Tx-Rx to easily adapt to various changes of target conditions and their surroundings.
A Review of Feature Selection and Classification Approaches for Heart Disease Prediction Fathania Firwan Firdaus; Hanung Adi Nugroho; Indah Soesanti
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 3 (2020): September 2020 (in progress)
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.59193

Abstract

Cardiovascular disease has been the number one illness to cause death in the world for years. As information technology develops, many researchers have conducted studies on a computer-assisted diagnosis for heart disease. Predicting heart disease using a computer-assisted system can reduce time and costs. Feature selection can be used to choose the most relevant variables for heart disease. It includes filter, wrapper, embedded, and hybrid. The filter method excels in computation speed. The wrapper and embedded methods consider feature dependencies and interact with classifiers. The hybrid method takes advantage of several methods. Classification is a data mining technique to predict heart disease. It includes traditional machine learning, ensemble learning, hybrid, and deep learning. Traditional machine learning uses a specific algorithm. The ensemble learning combines the predictions of multiple classifiers to improve the performance of a single classifier. The hybrid approach combines some techniques and takes advantage of each method. Deep learning does not require a predetermined feature engineering. This research provides an overview of feature selection and classification methods for the prediction of heart disease in the last ten years. Thus, it can be used as a reference in choosing a method for heart disease prediction for future research.
ECG Signal Classification Review Muhammad Rausan Fikri; Indah Soesanti; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.60295

Abstract

The heart is an important part of the human body, functioning to pump blood through the circulatory system. Heartbeats generate a signal called an ECG signal. ECG signals or electrocardiogram signals are basic raw signals to identify and classify heart function based on heart rate. Its main task is to analyze each signal in the heart, whether normal or abnormal. This paper discusses some of the classification methods which most frequently used to classify ECG signals. These methods include pre-processing, feature extraction, and classification methods such as MLP, K-NN, SVM, CNN, and RNN. There were two stages of ECG classification, the feature extraction stage and the classification stage. Before ECG features were extracted, raw ECG signal data first processed in the pre-processing stage because ECG signals were not necessarily free of noise. Noise will cause a decrease in accuracy during the classification process. After features were extracted, ECG signals were then classified with the classification method. Neural Network methods such as CNN and RNN are best to use since they can give better accuracy. For further research, the machine learning method needs to be improved to get high accuracy and high precision in the ECG signals classification.
Modified Usability Test Scenario: User Story Approach to Evaluate Data Visualization Dashboard Nurul Tiara Kadir; Rudy Hartanto; Selo Sulistyo
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.61201

Abstract

The data processing results are commonly displayed in a dashboard with various graphic visualization forms to deliver new knowledge easier to understand by users. However, many data analysis dashboards cannot communicate the knowledge effectively and efficiently given the unsuitable design implementation. Therefore, research to measure the interface display's effectiveness in the data analysis system is deemed necessary. This research proposed a scenario modification in the usability test with a user story approach to measuring the system interface display in delivering the information to users. The approach of a usability test with the user story is expected to be capable of helping the researcher in understanding the user habits indirectly. There were 20 participants to validate the proposed method. Participants were asked to use the system and answer several questions to develop their user experience. After developing user experience for each user, the System Usability Scale (SUS) was conducted. SUS score results obtained from this research was 75.25. Besides, the researcher also measured the understanding level among the users using questionnaires. The questionnaire results were converted into numbers and resulted in a mean value of 91.8. Those two values indicate the users' ability to use the system well and obtain the new knowledge displayed in the data analysis dashboard.
A Review on Face Anti-Spoofing Rizky Naufal Perdana; Igi Ardiyanto; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.61827

Abstract

The biometric system is a security technology that uses information based on a living person's characteristics to verify or recognize the identity, such as facial recognition. Face recognition has numerous applications in the real world, such as access control and surveillance. But face recognition has a security issue of spoofing. A face anti-spoofing, a task to prevent fake authorization by breaching the face recognition systems using a photo, video, mask, or a different substitute for an authorized person's face, is used to overcome this challenge. There is also increasing research of new datasets by providing new types of attack or diversity to reach a better generalization. This paper review of the recent development includes a general understanding of face spoofing, anti-spoofing methods, and the latest development to solve the problem against various spoof types.
Serendipity Identification Using Distance-Based Approach Widhi Hartanto; Noor Akhmad Setiawan; Teguh Bharata Adji
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.62344

Abstract

The recommendation system is a method for helping consumers to find products that fit their preferences. However, recommendations that are merely based on user preference are no longer satisfactory. Consumers expect recommendations that are novel, unexpected, and relevant. It requires the development of a serendipity recommendation system that matches the serendipity data character. However, there are still debates among researchers about the available common definition of serendipity. Therefore, our study proposes a work to identify serendipity data's character by directly using serendipity data ground truth from the famous Movielens dataset. The serendipity data identification is based on a distance-based approach using collaborative filtering and k-means clustering algorithms. Collaborative filtering is used to calculate the similarity value between data, while k-means is used to cluster the collaborative filtering data. The resulting clusters are used to determine the position of the serendipity cluster. The result of this study shows that the average distance between the recommended movie cluster and the serendipity movie cluster is 0.85 units, which is neither the closest cluster nor the farthest cluster from the recommended movie cluster.
Image Analysis for MRI-Based Brain Tumor Classification Using Deep Learning Krisna Nuresa Qodri; Indah Soesanti; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.62663

Abstract

Tumors are cells that grow abnormally and uncontrollably, whereas brain tumors are abnormally growing cells growing in or near the brain. It is estimated that 23,890 adults (13,590 males and 10,300 females) in the United States and 3,540 children under the age of 15 would be diagnosed with a brain tumor. Meanwhile, there are over 250 cases in Indonesia of patients afflicted with brain tumors, both adults and infants. The doctor or medical personnel usually conducted a radiological test that commonly performed using magnetic resonance image (MRI) to identify the brain tumor. From several studies, each researcher claims that the results of their proposed method can detect brain tumors with high accuracy; however, there are still flaws in their methods. This paper will discuss the classification of MRI-based brain tumors using deep learning and transfer learning. Transfer learning allows for various domains, functions, and distributions used in training and research. This research used a public dataset. The dataset comprises 253 images, divided into 98 tumor-free brain images and 155 tumor images. Residual Network (ResNet), Neural Architecture Search Network (NASNet), Xception, DenseNet, and Visual Geometry Group (VGG) are the techniques that will use in this paper. The results got to show that the ResNet50 model gets 96% for the accuracy, and VGG16 gets 96% for the accuracy. The results obtained indicate that transfer learning can handle medical images.
Bidirectional Battery Interface in Standalone Solar PV System for Electrification in Rural Areas Yuwono Bimo Purnomo; F. Danang Wijaya; Eka Firmansyah
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 2 (2021): June 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.63471

Abstract

In a standalone photovoltaic (PV) system, a bidirectional DC converter (BDC) is needed to prevent the battery from damage caused by DC bus voltage variation. In this paper, BDC was applied in a standalone solar PV system to interface the battery with a DC bus in a standalone PV system. Therefore, its bidirectional power capability was focused on improving save battery operation while maintaining high power quality delivery. A non-isolated, buck and boost topology for the BDC configuration was used to interface the battery with the DC bus. PID controller-based control strategy was chosen for easy implementation, high reliability, and high dynamic performance. A simulation was conducted using MATLAB Simulink program. The simulation results show that the implementation of the BDC controller can maintain the DC bus voltage to 100 V, have high efficiency at 99.18% in boost mode and 99.48% in buck mode. To prevent the battery from overcharging condition, the BDC stops the charging process and then works as a voltage regulator to maintain the DC bus voltage at reference value.
Dimmable High Power LED Driver Using Fuzzy Logic Controller Rizky Fatur Rochman; Eka Prasetyono; Rachma Prilian Eviningsih
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 2 (2021): June 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.63772

Abstract

The use of lighting loads is one of the crucial matters which increases every year. The increasing use then leads to the development of brighter and longer-lasting sources. In addition, the conventional use of lighting loads today, which only emit light at its maximum intensity, does not allow the consumers to adjust the brightness level as needed. Consequently, this condition may cause energy wastage. The LED lighting system is gaining popularity as it is widely used in a wide range of applications. The advantages of LEDs, such as its compact size and varied lamp colors, replace conventional lighting sources. The linear setting of the driver topology using the flyback converter was aimed to control the LEDs with a constant current in order to adjust the variation of the LED light intensity. The closed-loop driver circuit with flyback converter topology was designed as an LED driver with a given load specification from the LED string. A dimmable feature was included for adjusting the intensity of the light produced by the LEDs. Eventually, the fuzzy logic controller (FLC) method was applied to the integrated change setting to obtain a dynamic response.
Analysis of Information Technology Security Management UKSW SIASAT Using ISO/IEC 27001:2013 Andeka Rocky Tanaamah; Friska Juliana Indira
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 2 (2021): June 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.65670

Abstract

IT security management is essential for organizations to notice the occurring risks and opportunities because they will profoundly affect the ongoing business processes within the organization. The Satya Wacana Academic Information System, more often called SIASAT, is an IT component playing an essential role in running core business processes at Satya Wacana Christian University under the control of the Information Systems and Technology Bureau. At this time, the implementation of SIASAT has been going well, but there are still some obstacles. Lack of human resources is one of the findings and one it becomes of the most significant risks as it affects the use of infrastructure and information security. This research was conducted using the international standard ISO/IEC 27001:2013, prioritizing information security by taking a planning clause focusing on risk assessment. From the results of this study, there were nine recommendations given. Some of which were the most important, i.e., creating separated standard operating procedure documents for SIASAT, which previously were still affiliated with the Academic Administration Bureau; distributing job descriptions; and providing clear and documented access rights for everyone. It is expected that this research can reduce the occurring risks and can be considered for establishing improvements to enhance academic services in the future.

Page 8 of 10 | Total Record : 93

 6   7   8   9   10 

Filter by Year

2017 2021


Reset
Filter By Issues
All Issue Vol 5, No 4 (2021): December 2021 Vol 5, No 3 (2021): September 2021 Vol 5, No 2 (2021): June 2021 Vol 5, No 1 (2021): March 2021 Vol 4, No 3 (2020): September 2020 (in progress) Vol 4, No 2 (2020): June 2020 Vol 4, No 1 (2020): March 2020 Vol 3, No 4 (2019): Desember 2019 Vol 3, No 3 (2019): September 2019 Vol 3, No 2 (2019): June 2019 Vol 3, No 1 (2019): March 2019 Vol 2, No 4 (2018): December 2018 Vol 2, No 3 (2018): September 2018 Vol 2, No 2 (2018): June 2018 Vol 2, No 1 (2018): March 2018 Vol 1, No 4 (2017): December 2017 Vol 1, No 3 (2017): September 2017 Vol 1, No 2 (2017): June 2017 Vol 1, No 1 (2017): March 2017 More Issue