cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,174 Documents
 722   723   724   725   726 
Liver fibrosis processing, multiclassification, and diagnosis based on hybrid machine learning approaches Zainab Sattar Jabbar; Auns Qusai Al-Neami; Ahmed A. Khawwam; Sufian Munther Salih
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1614-1622

Abstract

The cirrhosis and cirrhosis-related problems are connected to the degree of fibrosis in the liver. The purpose of this paper is to propose an automated method for identifying liver fibrosis using ultrasound shear wave elastography (700) images that is based on a hybrid machine learning approach using a convolutional neural network (CNN) with two types of classifier (SoftMax and support vector machine (SVM)). The dataset gathered from hospitals is used in the training and testing phases of the model. The objective is to develop a hybrid machine learning model that can classify images based on their stage of fibrosis. The suggested system comprises three stages. The first is the preprocessing step, which starts with countor detection and continues with the "contrast limited adaptive histogram equalization (CLAHE)" technique to show the properties of liver tissue. In the second step, the CNN algorithm was utilized, which was based on several images to extract deep features and identify shear wave elastography (SWE) samples. In the third step, SVM and SoftMax functions are used to classify liver fibrosis. A five-class model (normal, F1, F2, F3, and F4) was developed. The result illustrates how successfully the CNN-SoftMax and CNN-SVM classifiers classified liver fibrosis in the test dataset, with 97.18% and 98.59% accuracy, respectively.
Vote algorithm based probabilistic model for phishing website detection Md. Sazzadul Islam Islam Prottasha; Md. Zihadur Rahman; ABM Kabir Hossain; Samia Ferdous Mou; Md. Bulbul Ahmed; M. Shamim Kaiser
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1582-1591

Abstract

Internet scams have been a major concern for everyone over the past decade. With the advancement of technology, attackers have formulated different kinds of contemporary fraudulent procedures to obtain user’s sensitive information. Phishing is one of the oldest and common fraudulent attempts by which every year millions of internet users fall victim to scams resulting in losing their money. Different techniques and algorithms have been proposed by researchers in detecting phishing websites. However, the detection of phishing websites has few challenges since there are different subjective considerations and ambiguities involved in the detection process. This paper presents a two-stage probabilistic method for detecting phishing websites based on the vote algorithm. In the first stage, 29 different base classifiers have been used and their probabilistic values were calculated. In the second stage, the voting algorithm aggregated the probabilistic values of several base classifiers and the phishing websites were detected using the average of probabilities approach. The voting technique achieved an accuracy of 97.431% outperforming all of the single base classifiers in terms of accuracy.
Non-isolated high voltage gain DC to DC converter based on the diode a capacitor switches Ibraheem Jawad Billy; Jasim Farhood Hussein
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp67-75

Abstract

Many researchers have put great endeavor to develop DC converter’s designs, into studying how to increase voltage gain with low switching stress and low ripple current. This paper has proposed a circuit to boost the voltage with a high gain conversion ratio. It is a combined adverse parallel two boost conversion. Two inductors are connected on both sides of the input source to decrease the current-ripple of the input current and output sides utilizing the interleaving technique. The proposed converter integrated with an active-network circuit is based on multiplier cells and two output capacitors. The voltage gain and voltage stresses across power semiconductors have been determined using a steady-state analysis. In addition, the input current- ripple and output voltage-ripple are analysis have been reported. This converter's inductors operate in a continuous conduction mode (CCM). The designed converter is capable of achieving significant voltage gain while maintaining a low duty ratio. Furthermore, the active switches and output diodes are under low voltage stress. As a result, low voltage components can be used to decrease conduction loss and cost. Finally, this converter was simulated in MATLAB/Simulink software to verify the theoretical calculations.
Implementation of augmented reality on historical monuments in Gorontalo Province Moh Ramdhan Arif Kaluku; Nikmasari Pakaya; Galang Leoni Yagri Ms Punu
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp559-566

Abstract

Several historical monument buildings in the city of Gorontalo with important colonial historical features have been designated as cultural reserves. The unavailability of information media that can be accessed by visitors so that visitors do not know in detail about the historical place visited, by implementing augmented reality (AR) technology as access to information media using multimedia development life cycle (MDLC) methods, visitors can access information freely and in real time, by presenting information and also displaying three-dimensional (3D) monument buildings with android devices. Based on research conducted, the design of AR applications is used to create an information media, and also one of the methods of introducing gorontalo historical monuments that can be used for prospective visitors outside the area and within the area. Implementing AR on historical monuments in Gorontalo Provides a new alternative, in utilizing technology by providing an information medium for historical monuments in Gorontalo.
Adaptive doubly fed induction generator’s control driven wind turbine using luenberger observer optimized by genetic algorithm Hind Elaimani; Ahmed Essadki; Noureddine Elmouhi; Fadoua Bahja
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp120-132

Abstract

The calculation of control parameters for a system control method is based on the model of the system with assumed fixed internal parameters. However, these parameters can vary greatly due to several phenomena. This paper presents an adapted control of a doubly fed induction generator machine robust against the rotor resistance variations of the machine used as a generator in wind energy conversion systems. The adaptation is ensured by a system allowing to identify in real time the value of the resistance, the system used is mainly based on a Luenberger observer. The conversion system is divided into two parts, the first mechanical part containing the turbine and the gearbox, the second electrical one consisting of a double fed induction generator, linked on the stator side directly to the grid, and on the rotor, side linked to the grid through two power electronics converters interposed with a direct current (DC) link. The machine-side converter is used to control the active and reactive powers, and the second on the grid side is used to control the DC link voltage. The converters are controlled by the sliding mode strategy, and the validity of the methods is checked by simulation using MATLAB/Simulink.
Empirical evidence of phishing menace among undergraduate smartphone users in selected universities in Nigeria Maureen Ifeanyi Akazue; Arnold Adimabua Ojugo; Rume Elizabeth Yoro; Bridget Ogheneovo Malasowe; Obinna Nwankwo
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1756-1765

Abstract

In our exploratory quasi-experimental study, 480-student were recruited and exposed to social engineering directives during a university orientation week. The directives phishing attacks were performed for 10 months in 2021. The contents attempted to elicit personal user-data from participants, enticing them to click compromised links. The study aimed to determine cybercrime risks among undergraduates in selected universities in Nigeria, observe responses to socially-engineered attacks, and explore their attitudes to cybercrime risks before/after such attacks. The study generalized that all participants have great deal awareness of cybercrime, and also primed all throughout study to remain vigilant to scams. The study explores various types of scam and its influence on students’ gender and age on perceived safety on susceptibility to phishing scams. Results show that contrary to public beliefs, none of these factors were associated with scam susceptibility and vulnerability rates of the participants.
The role of web engineering in e-learning application development: a review study Hussin Ahmad Hamzah; Muhamad Sadry Abu Seman
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1576-1588

Abstract

Web engineering is a growing multidisciplinary paradigm that has hardly begun to curiosity the interest, researchers, and other key actors involved in developing web-based systems. Therefore, the effect of web engineering applications on e-learning systems should be investigated to guarantee that the web’s potential for supporting the learning process is appropriately used. The objective of the study highlights the advantages, benefits, and contributions of web engineering in developing e-learning systems. This is qualitative research. The primary data was collected via an in-depth study of pertinent research studies. The second tool was an interview with the e-learning systems developers. The results showed that the most influential web engineering tools to develop e-learning systems. Moreover, the main areas of development of e-learning systems include changing the learning environment characteristics, changing student behaviour, changing roles, and incorporating artificial intelligence (AI). The results also showed that web applications' main challenges in e-learning systems include technologies, adaptability, lack of experience and training, lack of funding, changing student preferences and needs, the gap between the mobile and computer versions, and security threats, job-overload, and time. It was found that web engineering has a significant role in developing e-learning applications.
Towards a new method of estimating the student attention based on the eye gaze Tarik Hachad; Abdelalim Sadiq; Fadoua Ghanimi; Lamiae Hachad; Ahmed Laguidi
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp867-877

Abstract

This paper presents a new system for automating the monitoring and estimation of student attention during the course session. The followed approach is based on the analysis of the student's gaze to predict his state of attention. A simple hardware device consisting of a camera and a pc was used in this study. Existing machine learning algorithms were used for the student gaze estimation. The principles of homography were used to ensure the transformation from an image coordinates system to a real-world coordinates system. 5 students took part in this experiment and whose gaze was detected and analyzed during 10 minutes of the class session in order to analyze their states of attention and inattention.
New algorithm for localization of iris recognition using deep learning neural networks Ekbal Hussein Ali; Hanadi Abbas Jaber; Nahida Naji Kadhim
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp110-119

Abstract

Iris recognition is the most reliable and accurate method for eye identification. A novel strategy for localizing iris printing is proposed in this paper. The median filter and histogram were used for this purpose. To extract iris features from iris photographs, an algebraic method known as semi-discrete matrix decomposition (SDD) is used. For classification, neural network (NN) is used to extract the SDD feature. This study also included the setup of convolution neural network (CNN), a convolution neural network that does not require feature extraction, as well as a comparison of the two types of classifiers is made. Iris images are obtained from the Chinese Academy of Sciences Institute of Automation dataset (CASIA Iris-V1), a common database used for the iris recognition system. The proposed algorithm is straightforward, simple, efficient, and fast. The experimental results showed that the proposed algorithm achieved high classification accuracy of approximately 95.5% and 95% for CNN and NN based on SDD features respectively. The proposed algorithms outperformed literature works and required less time for determining the location of iris region.
A secure framework of blockchain technology using CNN long short-term memory hybrid deep learning model Gillala Chandra Sekhar; Aruna Rajendran
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1786-1795

Abstract

Generation Z is embracing blockchain technology, which is appropriate for the digital age. Internet of things (IoT) can benefit from blockchain technology IoT. The proliferation of IoT technology has led to breakthroughs in distributed system architecture. For the blockchain network to store, communicate, and exchange data, it needs a randomized data management system. This shows how difficult it may be to provide consistent and safe data replication in a distributed system, an issue blockchain technology may overcome. We need a solid prediction model that improves results. This article describes an innovative way to overcome the limitations of third-party transactions using Bitcoin. In this article, convolutional neural networks-long short term memory (CNN-LSTM) deep learning forecasting models are introduced. Convolutional layers help extract relevant data from instances. It has an long short-term memory (LSTM) layer, which lets it find long-and short term dependencies. The experiment's goal was to test the multivariate statistical model we suggested and compare its performance to well-established models. The addition of convolutional layers to a forecasting model may improve its accuracy, according to an experiment. The research shows that this strategy has a better chance of success and is more trustworthy than others.

Page 724 of 918 | Total Record : 9174

 722   723   724   725   726 

Filter by Year

2012 2026


Reset
Filter By Issues
All Issue Vol 41, No 2: February 2026 Vol 41, No 1: January 2026 Vol 40, No 3: December 2025 Vol 40, No 2: November 2025 Vol 40, No 1: October 2025 Vol 39, No 3: September 2025 Vol 39, No 2: August 2025 Vol 39, No 1: July 2025 Vol 38, No 3: June 2025 Vol 38, No 2: May 2025 Vol 38, No 1: April 2025 Vol 37, No 3: March 2025 Vol 37, No 2: February 2025 Vol 37, No 1: January 2025 Vol 36, No 3: December 2024 Vol 36, No 2: November 2024 Vol 36, No 1: October 2024 Vol 35, No 3: September 2024 Vol 35, No 2: August 2024 Vol 35, No 1: July 2024 Vol 34, No 3: June 2024 Vol 34, No 2: May 2024 Vol 34, No 1: April 2024 Vol 33, No 3: March 2024 Vol 33, No 2: February 2024 Vol 33, No 1: January 2024 Vol 32, No 3: December 2023 Vol 32, No 1: October 2023 Vol 31, No 3: September 2023 Vol 31, No 2: August 2023 Vol 31, No 1: July 2023 Vol 30, No 3: June 2023 Vol 30, No 2: May 2023 Vol 30, No 1: April 2023 Vol 29, No 3: March 2023 Vol 29, No 2: February 2023 Vol 29, No 1: January 2023 Vol 28, No 3: December 2022 Vol 28, No 2: November 2022 Vol 28, No 1: October 2022 Vol 27, No 3: September 2022 Vol 27, No 2: August 2022 Vol 27, No 1: July 2022 Vol 26, No 3: June 2022 Vol 26, No 2: May 2022 Vol 26, No 1: April 2022 Vol 25, No 3: March 2022 Vol 25, No 2: February 2022 Vol 25, No 1: January 2022 Vol 24, No 3: December 2021 Vol 24, No 2: November 2021 Vol 24, No 1: October 2021 Vol 23, No 3: September 2021 Vol 23, No 2: August 2021 Vol 23, No 1: July 2021 Vol 22, No 3: June 2021 Vol 22, No 2: May 2021 Vol 22, No 1: April 2021 Vol 21, No 3: March 2021 Vol 21, No 2: February 2021 Vol 21, No 1: January 2021 Vol 20, No 3: December 2020 Vol 20, No 2: November 2020 Vol 20, No 1: October 2020 Vol 19, No 3: September 2020 Vol 19, No 2: August 2020 Vol 19, No 1: July 2020 Vol 18, No 3: June 2020 Vol 18, No 2: May 2020 Vol 18, No 1: April 2020 Vol 17, No 3: March 2020 Vol 17, No 2: February 2020 Vol 17, No 1: January 2020 Vol 16, No 3: December 2019 Vol 16, No 2: November 2019 Vol 16, No 1: October 2019 Vol 15, No 3: September 2019 Vol 15, No 2: August 2019 Vol 15, No 1: July 2019 Vol 14, No 3: June 2019 Vol 14, No 2: May 2019 Vol 14, No 1: April 2019 Vol 13, No 3: March 2019 Vol 13, No 2: February 2019 Vol 13, No 1: January 2019 Vol 12, No 3: December 2018 Vol 12, No 2: November 2018 Vol 12, No 1: October 2018 Vol 11, No 3: September 2018 Vol 11, No 2: August 2018 Vol 11, No 1: July 2018 Vol 10, No 3: June 2018 Vol 10, No 2: May 2018 Vol 10, No 1: April 2018 Vol 9, No 3: March 2018 Vol 9, No 2: February 2018 Vol 9, No 1: January 2018 Vol 8, No 3: December 2017 Vol 8, No 2: November 2017 Vol 8, No 1: October 2017 Vol 7, No 3: September 2017 Vol 7, No 2: August 2017 Vol 7, No 1: July 2017 Vol 6, No 3: June 2017 Vol 6, No 2: May 2017 Vol 6, No 1: April 2017 Vol 5, No 3: March 2017 Vol 5, No 2: February 2017 Vol 5, No 1: January 2017 Vol 4, No 3: December 2016 Vol 4, No 2: November 2016 Vol 4, No 1: October 2016 Vol 3, No 3: September 2016 Vol 3, No 2: August 2016 Vol 3, No 1: July 2016 Vol 2, No 3: June 2016 Vol 2, No 2: May 2016 Vol 2, No 1: April 2016 Vol 1, No 3: March 2016 Vol 1, No 2: February 2016 Vol 1, No 1: January 2016 Vol 16, No 3: December 2015 Vol 16, No 2: November 2015 Vol 16, No 1: October 2015 Vol 15, No 3: September 2015 Vol 15, No 2: August 2015 Vol 15, No 1: July 2015 Vol 14, No 3: June 2015 Vol 14, No 2: May 2015 Vol 14, No 1: April 2015 Vol 13, No 3: March 2015 Vol 13, No 2: February 2015 Vol 13, No 1: January 2015 Vol 12, No 12: December 2014 Vol 12, No 11: November 2014 Vol 12, No 10: October 2014 Vol 12, No 9: September 2014 Vol 12, No 8: August 2014 Vol 12, No 7: July 2014 Vol 12, No 6: June 2014 Vol 12, No 5: May 2014 Vol 12, No 4: April 2014 Vol 12, No 3: March 2014 Vol 12, No 2: February 2014 Vol 12, No 1: January 2014 Vol 11, No 12: December 2013 Vol 11, No 11: November 2013 Vol 11, No 10: October 2013 Vol 11, No 9: September 2013 Vol 11, No 8: August 2013 Vol 11, No 7: July 2013 Vol 11, No 6: June 2013 Vol 11, No 5: May 2013 Vol 11, No 4: April 2013 Vol 11, No 3: March 2013 Vol 11, No 2: February 2013 Vol 11, No 1: January 2013 Vol 10, No 8: December 2012 Vol 10, No 7: November 2012 Vol 10, No 6: October 2012 Vol 10, No 5: September 2012 Vol 10, No 4: August 2012 Vol 10, No 3: July 2012 More Issue