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 68 Documents
 3   4   5   6   7 
Search results for , issue "Vol 20, No 1: October 2020" : 68 Documents clear
An evaluation of the accelerometer output as a motion artifact signal during photoplethysmograph signal processing control Muhideen Abbas Hasan; Munther Naif Thiyab; Settar S. Keream; Uzba H, Salaman; Kaleid W. Abid
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp125-131

Abstract

Photoplethysmography (PPG) sensors are widely used in medical applications due to their attractive properties such as non-invasiveness, inexpensive, and easy setup. However, they are still inefficient in non-stationary states of important measurements related to cardiovascular assessment.  Adaptive noise cancellation (ANC) has existed as a kind of technique to address this issue. Unfortunately, the traditional 3-Axis Accelerometer (ACC) in ANC implementation has failed to provide the real motion artifact (MA) as the main factor for efficient adaptive filtering. In this work, the performance of ACC will be investigated and compared with a new twin photodiodes PPG probe design (TPs-PPD) that has been proven in previous work. The TPs-PPD contained an added covered photodiode (CPD) customized to obtain the MA instead of classic use of ACC. During different motions, PPG data were recorded and processed at the same time by the same two units of adaptive filters using ACC and CPD as noise references. The results indicated a clear failure of the ACC compared to the CPD in determining important features of PPG signal, in addition to the accuracy of signal to noise ratio (SNR) and mean square error (MSE). The CPD was better than ACC as it reduced the MSE by 14 times while the SNR was multiplied 10 times. Without any doubt, it has been proven with evidence that the ACC is not suitable for the processing of human health-related signals while PPG can be used for such purposes.
IOT-Based smart street lighting enhances energy conservation Zakiah Mohd Yusoff; Zuraida Muhammad; Mohd Syafiq Izwan Mohd Razi; Noor Fadzilah Razali; Muhd Hussaini Che Hashim
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp528-536

Abstract

The electricity generation cost is escalating every year while the electric energy is indispensable and increasing in demand. The resources for energy generation is also depleting due to the increasing demand of power. Thus, a system that can reduce the energy wastage and the massive expenses is essential. Street light system is one of the systems that can reduce energy consumption. The massive energy consumption from the current street light system is not efficient enough to reduce the wasted energy. By implementing an IOT-based smart street light system, the power consumption of the street light will be optimized. This system will also provide the ability to monitor input voltage for Arduino MEGA 2560 microcontroller and control the street light through IOT. The concept of this smart system is to introduce an intelligent system which can decide to switch on or off the street light according to the movement detection by using an infrared sensor module. The data will be sent to Arduino Mega 2560, which is a microcontroller that will decide to turn on or off the street light. The Wi-Fi module ESP-01 is implemented to enable the microcontroller to connect to Blynk software for monitoring and controlling purpose. The result shows that the smart street light system is expected to reduce energy consumption up to 45.48% on weekdays and 32.22% on weekends from the present street light system which uses timer system. The IOT-based Smart Street Light system also shows the condition of the street light system based on the Blynk interfaces for maintenance purpose.
Mitigation of magnetising inrush current in three–phase power transformer Mudita Banerjee; Anita Khosla
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp39-45

Abstract

During energization of no – load transformers, a high and peaky current flow on the primary side which has rich second harmonics. This current is magnetising inrush current and it is generated when transformer core is driven deep into saturation. This current has various disturbances on transformer attribute; reduced life-span, major voltage drop, insulation weakening, electrical and mechanical vibrations in coils, difficulties in protecting relays and all leads to poor power quality of the electric system. This paper presents the analysis and comparison of recent techniques to reduce the magnitude of inrush current during energization of power transformer. The simulation results are provided for Pre – insertion of resistors, Controlled swithing and Pre – fluxing method. The best method is suggested for mitigating inrush current by simulating in MATLAB/SIMULINK environment.
Unequal clustering algorithm with IDA* multi-hop routing to prevent hot spot problem in WSNs Ahmed A. Alkadhmawee; Mohammed A. Altaha; Wisam Mahmood Lafta
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp445-453

Abstract

Energy conservation techniques are considered as the primary means of lengthening the lifetime of wireless sensor networks (WSNs). Clustering is a useful technique that achieves long-term operation of the network. Cluster heads that are near the base station are expected to die early because they are responsible for collecting data that comes from far away in addition to their own data, thereby leading to problem of hot spot in the WSN.This paper presents a new protocol that uses an unequal clustering algorithm with an IDA* routing method to address the hot spot problem. The base station divides the network into three levels of unequal sizes of clusters. The base station takes into consideration the energy level and the distance from the base station for cluster-head selection in each cluster. The cluster head will be changed based on the energy threshold for each cluster. The proposed method uses an IDA* algorithm for efficient multi-hop routing in the network. The uneven clustering algorithm reduces the energy consumption of the nodes, thereby minimising the hot spot problem. The obtained simulation results prove that our approach increases the load balancing, improves the stability and prolongs the network lifetime compared with other related approaches. 
Real-time object control system using open source platform Chang-Gyu Cgseong; Jung-Yee Kim; Doo-Jin Park
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp313-319

Abstract

Recently, the internet of things (IoT) has received great attention, and the demand for IOT applications in various fields is increasing. But drawbacks of IoT, such as having to use dedicated equipment and having to pay for a flat fee monthly, do not satisfy the consumers’ demands. These shortcomings of IoT is causing the appearance of users who try to design the environment of IoT that responds their demands and naturally, attempts to have monitoring system through open-source hardware like Arduino. Open source hardware has attracted a great deal of attention for the diffusion of the Internet of things as a key element of the Internet construction. The emergence of open source hardware, which has the advantage of low cost and easy and fast development, has made it possible to embody the idea of object Internet application services. In this paper, we design and implement a system that controls the objects in real time using open source hardware and MQTT protocol.
Pre-trained classification of scalp conditions using image processing Shafaf Ibrahim; Zarith Azuren Noor Azmy; Nur Nabilah Abu Mangshor; Nurbaity Sabri; Ahmad Firdaus Ahmad Fadzil; Zaaba Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp138-144

Abstract

Scalp problems may occur due to the miscellaneous factor, which includes genetics, stress, abuse and hair products. The conventional technique for scalp and hair treatment involves high operational cost and complicated diagnosis. Besides, it is becoming progressively important for the payer to investigate the value of new treatment selection in the management of a specific scalp problem. As they are generally expensive and inconvenient, there is an increasing need for an affordable and convenient way of monitoring scalp conditions. Thus, this paper presents a study of pre-trained classification of scalp conditions using image processing techniques. Initially, the scalp image went through the pre-processing such as image enhancement and greyscale conversion. Next, three features of color, texture, and shape were extracted from each input image, and stored in a region of interest (ROI) table. The knowledge of the values of the pre-trained features is used as a reference in the classification process subsequently. A technique of support vector machine (SVM) is employed to classify the three types of scalp conditions which are alopecia areata (AA), dandruff and normal. A total of 120 images of the scalp conditions were tested. The classification of scalp conditions indicated a good performance of 85% accuracy. It is expected that the outcome of this study may automatically classify the scalp condition, and may assist the user on a selection of suitable treatment available.
ICT-supported for participatory engagement within E-learning community Noor Hida Natrah Aziz; Haryani Haron; Afdallyna Fathiyah Harun
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp492-499

Abstract

This paper presents ICT-supported for participatory engagement learning within the e-learning community. Effectively tools in e-Learning facilitate interactive learning and the achievement of desired learning outcomes for learners. However, the intensity of its usage is not very remarkable; there is a need to understand ICT- supported for learners from the perspectives of participatory engagement. Therefore, integrating suitable technology into e-learning is expected to strengthen learner's engagement within the e-learning community. The objective of the study is to identify technology that could effectively support learners' engagement. This study analyzes the available technology in the market to integrate into e-learning using the technology evaluation process. Interview sessions with experts were held to validated and suggested other technology uses in e-learning. This research is carrying out with three experts (academic staff) of the e-technologies within the University. This study uses semi-structured interviews to captured expert suggestions, knowledge, and expertise about technologies. Understanding learner's requirements toward technology are essential to ensure learners can reap the benefits of technology usage.  This study uses a thematical analysis to identify and organize key themes from qualitative data. The result reveals mobile technology, wireless technology, live streaming technology, authoring tool, summative assessment, cloud computing, gamification and Instagram is suitable technologies that support participatory engagement activities.
A review of internet of medical things (IoMT) - based remote health monitoring through wearable sensors: a case study for diabetic patients Omar AlShorman; Buthaynah AlShorman; Mahmood Al-khassaweneh; Fahad Alkahtani
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp414-422

Abstract

The latest advances and trends in information technology and communication have a vital role in healthcare industries. Theses advancements led to the internet of medical things (IoMT) which provides a continuous, remote and real-time monitoring of patients. The IoMT architectures still face many challenges related to the bandwidth, communication protocols, big data and data volume, flexibility, reliability, data management, data acquisition, data processing and analytics availability, cost effectiveness, data security and privacy, and energy efficiency. The goal of this paper is to find feasible solutions to enhance the healthcare living facilities using remote health monitoring (RHM) and IoMT. In addition, the enhancement of the prevention, prognosis, diagnosis and treatment abilities using IoMT and RHM is also discussed. A case study of monitoring the vital signs of diabetic patients using real-time data processing and IoMT is also presented. 
An optimise ELM by league championship algorithm based on food images Salwa Khalid Abdulateef; Taj-Aldeen Naser Abdali; Mohanad Dawood Salman Alroomi; Mohamed Aktham Ahmed Altaha
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp132-137

Abstract

This paper presents an optimisation of extreme learning machine by league championship algorithm based on food images. extreme learning machine (ELM) is an effective classifier because of the performance which is higher than other classifiers’ aspects. However, some important drawbacks still work as a hindrance like failure of optimal selection weights for the weights of the input-hidden layer and the output of the threshold. In spite of the wide number of problem-solving attempts, there was no solution to be considered effective. This paper presents the approach of hybrid learning and the League Championship Algorithm is used by for the purpose of selecting the input weights and the thresholds outputs. The experimental outcomes showed that the performance of proposed technique is superior as compared according to different scenarios of the measures to benchmark. The proposed method has achieved an overall accuracy of 95% for UEC food 100 dataset and 94% for UEC food 256 dataset comparing with 94% and 80% for baseline approaches.
Towards IR4.0 implementation in e-manufacturing: artificial intelligence application in steel plate fault detection Adeleke Abdullahi; Noor Azah Samsudin; Mohd Rasidi Ibrahim; Muhammad Syariff Aripin; Shamsul Kamal Ahmad Khalid; Zulaiha Ali Othman
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 1: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i1.pp430-436

Abstract

Fault detection is the task of discovering patterns of a certain fault in industrial manufacturing. Early detection of fault is an essential task in industrial manufacturing. Traditionally, faults are detected by human experts. However, this method suffers from cost and time. In this era of Industrial revolution IR 4.0, machine learning (ML) methods and techniques are developed to solve fault detection problem. In this study, three standard ML models: LR, NB, and SVM are developed for the classification problem. The experimental dataset used in this study consists of steel plates faults. The dataset is retrieved from UCI machine learning repository. Three standard evaluation methods: accuracy, precision, and recall are validated on the classification models. Logistic regression (LR) model achieved the highest accuracy and precision scores of 94.5% and 0.756 respectively. In addition, the SVM model had the highest recall score of 0.317. The results showed the significant impact of AI/ML approach in steel plates fault diagnosis problem. 

Page 6 of 7 | Total Record : 68

 3   4   5   6   7 

Filter by Year

2020 2020


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