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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
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Design of inception architecture for skin melanoma classification Sankarakutti Palanichamy Manikandan; Vedanandam Karthikeyan; Ganesamoorthy Nalinashini
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1372-1381

Abstract

The number of people diagnosed with skin cancer is increasing sharply. Both invasive and non-invasive methods of examination may be used to investigate it. However, the invasive method is more difficult for the patient because samples must be taken from the lesion itself, or the whole lesion must be cut out. It also requires more time and cost. To avoid invasive procedures, computer-based analysis and diagnosis have the potential to increase diagnostic accuracy and turnaround time. This study develops a unique discriminative deep learning architecture (DDLA) for dermoscopic image classification (DIC), called DDLA-DIC, which uses the concept of inception. Using this concept, the proposed DDLA-DIC system is designed wider and deeper and the network learns from various spatial patterns. The proposed DDLA-DIC system can extract image characteristics from dermoscopic images for skin cancer diagnosis in an effective and efficient way. The proposed DDLA-DIC system is evaluated by utilizing the dermoscopic images from the PH2 database, and the obtained classification results are based on a random split approach. The simulation results indicate that the framework has a great deal of potential with 99.79% accuracy.
Multi-objective optimization of slotted stator switched reluctance motor for electric vehicle application Saif Kh Al-Farhan; Omar Sh Al-Yozbaky
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1223-1233

Abstract

The popularity of electric vehicles (EVs) and hybrid electric vehicles (HEVs) is projected to increase as environmental consciousness rises. They have emerged as a potential substitute for traditional electrical machines like the switched reluctance motors (SRMs). SRMs are renowned for their low cost of production and maintenance, built-in fault tolerance, and simple design. Additionally, because the machine's rotor construction does not require copper coils or permanent magnets, production costs are significantly reduced. However, it has disadvantages, including as high non-linearity, high torque ripple, and acoustic noise production. In this research, a method for designing slotted stator teeth switched reluctance motors (SST-SRM) in EVs using a genetic algorithm (GA) optimization design with multiple targets is provided. In order to achieve the best possible balance between peak torque (Tp), average torque (Tavg), and efficiency, the developed optimization function is chosen. The stator/rotor pole arc angle and slot width/depth are chosen as the optimized variables. When compared to traditional SRM, the optimization results of proposed SST-SRM demonstrate improvements in peak torque (24.40%, 36.98%, 42.73%, and 42.45%), average torque (7.40%, 29.94%, 33.00%, and 33.62%), and efficiency (0.27%, 0.52%, 0.97%, and 1.03%).
Early fire detection technique for human being using deep learning algorithm Kannan Deeba; Sattianadan Dasarathan; Srinivasa Rao Kandula; Krishnasamy Selva Sheela; Ravindran Ramkumar; Nagarajan Ashokkumar; Dhandapani Karthikeyan
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1648-1655

Abstract

Fire and smoke detection in today’s world is a must, especially in clustered areas where a quick response can prevent significant damages and save lives. Early detection plays a significant role in preventing the fire from spreading by alerting the emergency response personnel. It may not be possible to install traditional fire and smoke detectors everywhere. As a result, incorporating fire and smoke detection into existing closed circuit television (CCTV) systems in various places can provide a warning to the appropriate authorities, allowing for quick action to prevent the fire from spreading. This work aims in developing an early fire and smoke prediction model with CCTV footage images and video frames. The images and videos are collected from multiple datasets available online. A convolutional neural network (CNN) model is developed for early detection and prevention of the spreading of fire and compares it with transfer learning models ResNet50 and VGG19. The model obtain an accuracy of around 94% using CNN model, 95% using VGG19 and 98% using ResNet 50. A model with high accuracy can replace traditional fire detection systems which can be both cost-effective and easy to implement to existing surveillance cameras.
Study and analysis of electric vehicles adoption: a middle eastern country as a case study Muzhir Shaban Al-Ani; Thabit Sultan Mohammed; Karim M. Aljebory
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1735-1743

Abstract

Adaption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) is an important choice that has many positive environmental and economic impacts, where, it helps in reducing exhaust emission, participation in dropping down the amount of noise pollution, and improving the air quality. With these encouraging impacts as well as the reduction in the price of fuel consumption, electric vehicles become at the top of car industry. A study on electric vehicles and their impact on improving the quality of environment is the main motive of this research. Selected theories and factors related to the electric vehicles’ adoption are investigated and analysed. The main factor that led to the spread of electric vehicles is the reliance on electric energy, so it is considered as zero emissions. But there is another effect, which is that these vehicles need continuous electric charging daily, which in turn needs to generate electricity, which leads to environmental pollution indirectly.
Islamic moderation in education and the phenomenon of cyberterrorism: a systematic literature review Syamsul Ma'arif; Hamidulloh Ibda; Farid Ahmadi; Nanang Qosim; Nur Alfi Muanayah
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1523-1533

Abstract

This article presents a systematic literature review on Islamic moderation in education to prevent cyberterrorism in the latest literature. The method used is the systematic literature review and preferred reporting items for systematic reviews and meta-analyses protocol with the stages of identification, screening, eligibility, inclusion, abstraction, and data analysis assisted by PoP 7, VOSviewer, and NVIVO 12 plus. The search results in Scopus contained 1,252 articles, then filtered according to compatible themes into 54. The topic findings are the concept of Islamic moderation, Islamic moderation in preventing cyberterrorism in education, cyberterrorism, cyberterrorism phenomenon, terrorism, religious moderation, wasatiyyah, peaceful coexistence, and counter-terrorism. The findings of the results mention that Islamic moderation is a way of religion according to the principles of the Quran and Sunnah, namely ummah wasatan, which is applied to education. Cyberterrorism phenomenon curs in various parts of the world, including in education, which is spread through cyberspace to intimidate, spread fear, and destroy the order of life in terrorist groups. Islamic moderation plays a role in preventing cyberterrorism in education through ideological approaches to radical organisations, accommodation of local culture, digital literacy, counter-narrative and deradicalisation, digital media mastery, digital media peaceful, and soft power deterrence. Future research needs to explore Islamic moderation according to the times.
Satellite mission to study the Van Allen belts Drishana Jhunjhunwalla; Debani Prasad Mishra; Jayanta Kumar Sahu; Dashmat Hembram; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1400-1407

Abstract

The Van Allen belts are said to be a pack of highly energetic particles which are extremely fatal to electronic systems and living beings. Very little information is known about them. Besides the data from past missions, it’s still not enough to draw any conclusion regarding the phenomenon of its shape, size, and density. The paper talks of a cost-effective satellite mission named Vansat to study the Van Allen belts in depth. The project aims to study the energetic particles, magnetic fields, and plasma waves in the radiation belts. The mission also focuses on having environment-friendly concepts demonstrated through the technologies along with a reduction in the complexity of the devices and instruments. Vansat consists of a dual satellite system-one satellite to study the inner belt and the other to study the outer belts. The octagonal geometry of the satellite along with wings and solar panels ensure aero dynamicity, energy saving as well as radiation shielding.
A scoping review of topic modelling on online data Mohd Mukhlis Mohd Sharif; Ruhaila Maskat; Zirawani Baharum; Kamaruzaman Maskat
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1633-1641

Abstract

With the increasing prevalence of unstructured online data generated (e.g., social media, online forums), mining them is important since they provide a genuine viewpoint of the public. Due to this significant advantage, topic modelling has become more important than ever. Topic modelling is a natural language processing (NLP) technique that mainly reveals relevant topics hidden in text corpora. This paper aims to review recent research trends in topic modelling and state-of-the-art techniques used when dealing with online data. Preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology was used in this scoping review. This study was conducted on recent research works published from 2020 to 2022. We constructed 5 research questions for the interest of many researchers. 36 relevant papers revealed that more work on non-English languages is needed, common pre-processing techniques were applied to all datasets regardless of language e.g., stop word removal; latent dirichlet allocation (LDA) is the most used modelling technique and also one of the best performing; and the produced result is most evaluated using topic coherence. In conclusion, topic modelling has largely benefited from LDA, thus, it is interesting to see if this trend continues in the future across languages.
Maximizing wireless sensor network lifetime through energy-efficient routing Prashanth Malligere Vishweshwaraiah; Prema Nisana Siddegowda; Shivashankar Rudraswamy
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1442-1450

Abstract

Wireless sensor networks (WSNs) are an emerging technology that has the potential to transform the way agricultural farms operate. However, deploying WSNs in agricultural farms presents a unique set of challenges. Limited coverage area, power source availability, data collection and processing, environmental factors, cost, and integration with existing systems are some of the potential problems that need to be addressed when deploying WSNs in agricultural farms. Hence, in this work, we have proposed a method for increasing the lifetime of the sensor network which will help also help to reduce the energy. The proposed method has been evaluated in terms of network lifetime of the sensor nodes, routing and communication overhead. The results have been compared with the existing M-LEACH method and the results show that there is an enhancement of 79.02% for average network lifetime. The results also show that the proposed method reduces the average routing and communication overhead by 49.17% and 38.37% respectively.
Quantifying quantitative correlation of provider selection influences cloud security Azlinda Abdul Aziz; Salyani Osman; Setyawan Widyarto; Suziyanti Marjudi; Nur Razia Mohd Suradi; Rahayu Handan
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1642-1647

Abstract

The cloud computing has been able to help users to access the data easily and effectively. However, cloud security is highly emphasized to cloud users to ensure data is securely stored. The cloud security can be handled well by chosen trusted cloud service provider in getting high impact on the cloud security. The relationship between cloud security with the provider selection is much needed to ensure the extent to which data is securely stored in a cloud. Therefore, in this paper the quantitative method was conducted to measure the correlation between the selected the right cloud service provider influence the cloud security. Thus, knowledgeable person in having the experiences in using the cloud service was taking from two institution of higher learning (IHL) as a respondent. In addition, variability and normality data analysis was firstly conducted to obtain the consistency of the data. Then, the correlation between cloud security factor and provider selection factor was conducted using spearman correlation matrix and scatter graph in identifying the closely and significant the value in influencing between the factors. Thus, the correlation relationship analysis result shown the selected the right cloud provider’s give higher impact to cloud security.
Cluster analysis of socio-economic factors and academic performance of school students Kapila Devi; Saroj Ratnoo
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1568-1577

Abstract

The objective of the paper is to examine the academic performance of students’ vis-a-vis socio-economic factors using clustering analysis. The grades obtained in the 10th class are taken as the measure of academic performance. The variables such gender, caste, parental education and occupation. are considered as the socio-economic indicators. Three clustering algorithems are employed. The K-medoid performs better in the validation process to form the groupings based on intra-cluster homogeneity and inter-cluster heterogeneity. The clustering analysis results in two interesting groups of the students. One of the clusters is dominated by the students of general category and the other one by the scheduled caste category. Next, the appropriate statistical tests are applied to determine the factors that significantly differ in the two clusters. Cluster analysis shows that caste, parents' education and occupation, and family income are the differentiating factors between the two groups. However, we are unable to establish significant difference between the academic performance of the two groups of students at a 5% significance. The research carried out in this paper may be beneficial for making policies to bridge the gap in the educational attainment of the students from deprived sections of society.

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