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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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Machine learning based smart weather prediction Rajasekaran Meenal; Kiruthic Kailash; Prawin Angel Michael; Jeyaraj Jency Joseph; Francis Thomas Josh; Ekambaram Rajasekaran
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.pp508-515

Abstract

Weather forecasting refers to the prediction of atmospheric conditions depending on a given time and location. Weather prediction is essential and it plays a significant role in many sectors namely energy and utililities, marine transportation, aviation, agriculture and forestry to a greater extent. Accurate weather forecast mechanism help the farmers for suitable planning of farming operations that will prevent crop losses. In this work, the weather parameters namely precipitation, relative humidity, wind speed and solar radiation were predicted for few Indian locations using the conventional temperature based empirical models and machine learning algorithms such as linear regression, support-vector machine (SVM) and decision tree. Forecasting of weather parameters, on which agriculture depends, will increase the overall yield and it helps farmers and agricultural-based businesses to plan better. From the current results, it is observed that machine learning (ML) based methods had a better prediction results than the physics based conventional models for weather forecasting with mean square error of 0.1397 and correlation coefficient of 0.9259. The objective of this work is to arrive at an optimized end result and a better weather prediction using the Machine learning models with lesser computational effort.
Refurbished and improvised model using convolution network for autism disorder detection in facial images Narinder Kaur; Ganesh Gupta
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp883-889

Abstract

The main quality of deep learning over conventional machine learning (ML) techniques empowers firsthand uses in processing of images, speech recognition, medical imaging, machine translation and robotics, computer vision, and numerous other fields. The purpose of this study is to assess algorithms of deep Learning for person with the disorder of autism. This disorder is developing disorder that causes significant communicative, social and behavioral difficulties in those who have it. In this research paper, the Enhanced version of convolution network is discussed. Visual geometry group (VGG), is one of model of the convolution neural network which has essential features of convolution neural network (CNN). The VGG 16 net is employed to calculate the processes that can be used to classify this disorder with improved accuracy. The preprocessing of the image data is done. The VGG 16 convolution network is used to classify between autism spectrum disorder (ASD) and Non-ASD. Finally, the algorithm's efficacy is considered based on its accuracy performance. The VGG 16 net algorithm produces better results with an accuracy of 68.54%, compared with the normal CNN algorithm.
Retired electric vehicle battery to reduce the load frequency control oscillation in the micro grid system Muhammad Abdillah; Rozan Haqi Pratama; Nita Indriani Pertiwi; Herlambang Setiadi
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.pp1266-1275

Abstract

The potential of a retired electric vehicle battery (REVB) is its capacity to provide backup power supply to the power system grid. This paper proposed energy storage system (ESS) based on REVB called retired battery energy storage system (retired BESS) to tackle the intermittent of renewable energy source such as wind turbine and dynamic load change. To examine the efficacy of the proposed technique, the load frequency control (LFC) of microgrid (MG) system is utilized in this study and the proposed technique is compared to conventional LFC controller, PI controllers, superconducting magnetic energy storage (SMES), and a new electric vehicle battery. The kind of retired BESS cell used in this study is Li-ion nickel manganese cobalt oxide (NMC) type with a state of charge as of 70%. The capacity of each cell for retired BESS is 38 Ah. From the simulation result, the use of retired BESS can reduce frequency oscillation, compress the settling time to reach steady state, and maintain the robustness of the MG system. A retired BESS has a minimum error performance index value compared to conventional LFC, proportional integral (PI) controller, and SMES.
Supervised learning through k-nearest neighbor, used in the prediction of university teaching performance Omar Chamorro-Atalaya; Nestor Alvarado-Bravo; Florcita Aldana-Trejo; Claudia Poma-Garcia; Carlos Aliaga-Valdez; Gutember Peralta-Eugenio; Abel Tasayco-Jala
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.pp1625-1634

Abstract

This study initially seeks to identify the most optimal supervised learning algorithm to be used in predicting the perception of teacher performance, and then to evaluate its performance indicators that validate its predictive capacity. For this, the Matlab R2021a software is used; the experimental results determine that the supervised learning algorithm K-Nearest Neighbor Weighted (Weighted KNN) will be correct in 98.10% in predicting the perception of teaching performance, this has been validated by carrying out two evaluations through its performance indicators obtained in the confusion matrix and the receiver operating characteristic (ROC) curve, in the first evaluation an average sensitivity of 97.9%, a specificity of 99.1%, an accuracy of 98.8% and a precision of 96.7% are observed, thus validating the ability of the Weighted KNN model to correctly predict the perception of teacher performance; while in the receiver operating characteristic (ROC) curve, values of the area under the curve (AUC) equal to 0.99 and 1 are obtained, with this it is possible to validate the capacity that the model will have to distinguish between the 4 classes of the perception of the university teaching performance.
Monitoring system of photovoltaic panels using 433 MHz radio frequency module Zaidan Didi; Ikram El Azami
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.pp115-123

Abstract

In this article, we presented an innovative study that allows direct monitoring of the main parameters of photovoltaic panels. Our study focuses on the skills of radio frequency modules to send the main parameters of photovoltaic cells. In this paper, we used an Esp32 microcontroller in the radio frequency (RF) transmitter block and an Arduino Uno board in the receiver block, in addition, to measure current, we used a current sensor, and to measure voltage, we implemented a voltage divider. After that, we calculated the power and the energy. Note that the various measured and calculated values are stored and used via the ThingSpeak platform. In comparison with similar studies, our achievement presents an` effective and inexpensive solution because its operating principle is based on radio frequency transmission, so it works perfectly even in the absence of the internet. Finally, our study was very well tested without detecting any abnormalities, and the results obtained are a perfect witness to our success.
Design and implementation of low-cost vein-viewer detection using near infrared imaging Abdulrafa Hussain Maray; Saba Qasim Hasan; Naqaa Luqman Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1039-1046

Abstract

There are some medicines and medical treatments that need to be injected into the human body through the blood vessels, and this requires placing the cannula in the patient’s body. The blood vessels in the human body differ from one person to another, and medical personnel face major problems in finding the blood vessels in most cases, because of The difference in skin color, where it is difficult to see the blood veins in the skin with black pigment, and it is difficult to find it in people with obesity because of the layers of fat, and in children and newborns because these veins are small. This study talks about finding a way to photograph these veins, see them by design and implementation low cost prototype used equipment that were recycled old device, such as a web camera, infrared lamps and overhead device, All of these devices are of low cost. Then process these images using binary image, histogram equalization, segmentation and threshold to detect these blood veins. The algorithms for edges images detecting are many and complex, this study used five methods to detect vein image, such as Sobel, Laplacian, Canny, Roberts, and Prewitt.
Nash equilibrium learning in non-cooperative reputation game in social networks Khadija Touya; Mohamed Baslam; Rachid El Ayachi; Mostafa Jourhmane
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.pp527-534

Abstract

Recently, people became more dependent on online social networks with the increasing use and the rapid development of information technology. Those environments constitute an important area where users interact and create communication ties to maintain their relationships. Furthermore, the time life of these relationships is depending on reputations of the users. Every source (information provider) has a reputation which depends on his frequency of publishing, but also the opinions given by the observers (others users) has an important impact on the determination of this reputation. Since, everyone is trying selfishly to keep a good reputation; a competition is met within these networks. This paper aims to solve this kind of competition through a game theoretic approach; we formulate the said competition as a non-cooperative game, demonstrate the uniqueness of the existent Nash Equilibrium which seems to be the convent solution in this case, then present results clarifying and illustrating the proposed modeling method.
Secure smart home automation and monitoring system using internet of things Mohamed Khudhair Al-Gburi; Laith Ali Abdul-Rahaim
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.pp269-276

Abstract

As a result of the rapid increase in the number of users in internet of things (IoT) technologies, IoT becomes one of the most important technologies that play an important and essential role in various areas of human life, it provides service over 24 hours. In this paper, the proposed system relies on the implementation of a set of sensors for the Internet of things, which accomplish tasks inside the home automation, for example, controlling the main door, boiler and lock, as well as the ability to control lighting and air, internal temperature sensors, it based on the Arduino, to collect multimedia data, and remote-controlled sensors. The proposed system provides an efficient way to control and monitor the various devices in the home for security and safety purposes, and through sensors that rely on wireless technologies. The results show the abnormal alarm notification for heathcare/security purposes with the distance as 27 cm, smoke carbon monoxide on indoor air quality as 10211 degree Co as 6256 degree, Liquefied petroleum gas as 5097 degree, the delayed 3.4 ms and network latency as 0.0012 seconds of alarm notification with long distance as 60 m and high packet delivery ratio as 98.7%.
Simulation with system dynamics on university student research Laberiano Andrade-Arenas; David Llulluy Nuñez; Alexi Delgado
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.pp396-404

Abstract

Currently, student research at the university under study is carried out from the first semesters until the student graduates, but it is necessary to make adjustments to its guidelines that include student research within a teaching-learning process. The objective of the research is to propose a model of student research, using causal diagrams and forrester diagram; then carry out a simulation of the projection from 2021 to 2026 with the variables, students, quality teachers in the research, completed work for publication in journal or conference; and thus index in Scopus or Web of Science. Besides, in the methodological part, the systems dynamics method was applied, based on the systemic approach. The research work is predictive, which was carried out with the Vensim software, obtaining as a result of the simulation, an increase in the production of complete Works by the students; where in 2026 around 300 articles will be published by the students. In addition, there will be about 12 full-time quality research professors and approximately 6,000 students in 2026. The conclusion reached in the research is that the model helps the authorities make decisions appropriately according to the forecasts made in the different scenarios made with the Vensim software.
Healthcare scenario: a new task scheduling algorithm in cloud computing environment Nidhi Bansal; Ajay Kumar Singh
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1095-1101

Abstract

Makespan and cost are the major factors in the current scenario and they generally upgrade the results to optimize the upcoming task processing by implementing the scheduling within the specified cloud platform. A new proposed agenda is being considered for a health care system to make the world healthier. The paper is designed to identify prior work as a health evaluator for the end user and act accordingly. It also satisfies the end user by providing demanded results and can establish trust between the system and the customer within a global era. By analyzing the COVID-pandemic situation in the digital world, things should be implemented in conjunction with healthcare and technology to serve things better. The proposed algorithm works on priority basis by analyzing the current patient condition and then implemented in CloudSim Toolkit. As per the results, the proposed steps are performing 50-70% better in terms of makespan and cost. Notable optimization has been accomplished by the proposed healthcare evaluator.

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