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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 65 Documents
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Search results for , issue "Vol 30, No 3: June 2023" : 65 Documents clear
Soil pH periodic assortment with smart irrigation using aerial triboelectric nanogenerator Dhandapani Karthikeyan; Deeba Kannan; Brindha Gunasekaran; Hemalatha Selvaraj; Saurabh Gupta; Ravindran Ramkumar; Krishnasamy Vijayakumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1348-1358

Abstract

The paper presents an idea on pre-emptively ascertaining the soil pH value on an agriculture field amalgaming drone for aerial photo and subsequent smart irrigation model with the help of internet of things (IoT). The drone used for the aerial footage (multispectral imaging) consists of specialized cameras with filters that would help in ascertaining vegetation and health of the crops in the agriculture land. The IoT device used in smart irrigation model consists of sensors which accumulate data and execute the commands given in a recurring fashion of delay. Moreover, the use of triboelectric nanogenerator (TENG) would help in feasible energy harvesting for agricultural land use.
Simulation of photovoltaic station interfacing scada within transmission line Zamzami Zamzami; Nelly Safitri; Muhammad Arhami; Naziruddin Naziruddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1269-1278

Abstract

In this paper, a developed simulation of a photovoltaic (PV) station that includes a PV module, a grid-connected inverter, a maximum power point tracking (MPPT) system, and a DC link capacitor was discussed. The MPPT uses a proportional integral derivative (PID) incremental conductance controller. Due to make it simple to control and monitor the PV station, Simulink dashboard is used to develop an interface that resembles a supervisory control and data acquisition (SCADA) system. Then the faults circumstances were simulated on one of the circuits of the double circuit transmission line using the faults combo box that is accessible in the interface. Then the cases were developed to examine the impact of various faults on the operation and control of the solar station. The developed cases namely normal circumstance, single-phase to ground fault circumstance, double-phase fault circumstance, and three-phase to ground fault circumstance, respectively. Three-phase voltage and current at given fault conditions have been measured to control voltage sag and swell. The active and reactive power are also measured due to obtain that they are injected or absorbed the power from and to the transmission line and maintain toward their setpoint values as indications while the faults occurred.
Lighting level and room temperature audit of a University Campus Enalyn T. Domingo; Ferdinand L. Marcos; Cid L. Lapuz
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1279-1286

Abstract

An energy audit on a campus was conducted focusing on two parameters: lighting level and temperature. A walk-through survey for each room was done to measure the said parameters. The measurements were then compared with existing standards. It was found out that most of the rooms have lower than the standard average illumination. Meanwhile, there are rooms that have temperatures higher than the recommended values. Proposed improvements include adding lamps and change of T8 to T5 fluorescent bulbs. To address high temperature in the building, simple solutions like door closers and PVC roll curtains are suggested. Further study on the airtightness of the buildings and surface reflectance is recommended.
Malicious attacks modelling: a prevention approach for ad hoc network security Hasanien Ali Talib; Raya Basil Alothman; Mazin S. Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1856-1865

Abstract

As a result of the expansions that have taken place in the field of networking and the increase in the number of users of networks, there have recently been breakthroughs made in the techniques and methods used for network security. In this paper, a virtual private network (VPN) is proposed as a means of providing the necessary level of security for particular connections that span across vast networks. After the network performance metrics such as time delay and throughput have been accomplished, the suggested VPN is recommended for the purpose of assuring network security. In addition, artificial intelligence attack predictors and virtual private networks have been implemented with the purpose of preventing harmful activity within such connections. Using a wide variety of machine learning methods like Random Forests and Nave Bays, malicious assaults of any kind can be identified and thwarted in their tracks. Another technique for anticipating attacks is the use of an artificial neural network, which is a type of system that engages in deep learning and learns the behaviors of attacks while it is being trained so that it can then predict attacks. The results of this study demonstrate that the use of machine learning and artificial intelligence techniques can significantly improve the security and performance of virtual private networks and can effectively identify and prevent malicious attacks on networks.
Gaussian kernelized feature selection and improved multilayer perceptive deep learning classifier for software fault prediction Sureka Sivavelu; Venkatesh Palanisamy
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1534-1547

Abstract

Software fault prediction is the significant process of identifying the errors or defects or faults in a software product. But, accurate and timely detection is the major challenging issue in different existing approaches to predicting software defects. A novel Gaussian linear feature embedding-based statistical test piecewise multilayer perceptive deep learning classifier (GLFE-STPMPDLC) is introduced to improve software fault prediction accuracy and minimize time consumption. First, the input data are collected from the dataset. Next, the software metrics selection is carried out to select the significant metrics using Gaussian kernelized locally linear embedding with lesser software fault prediction. Then classification is carried out by Kaiser Meyer piecewise multilayer perceptive deep learning classifier for software fault prediction. The novelty of Kaiser–Meyer–Olkin (KMO) correlation test analyzes testing and training instances. The innovation of the Heaviside step activation function is applied for analyzing the KMO correlation test results and providing the final software fault prediction results. Finally, accurate fault prediction outcomes are achieved at the output layer with lesser error. Simulation of proposed GLFE-STPMPDLC technique achieves better 5%, 3%, 3% and 3% enhancement of fault prediction accuracy, precision, recall, and f-measure and 13% faster prediction time compared to conventional methods.
Design of a optimization algorithm for binary classification Miguel Angel Cano Lengua; Erik Alex Papa Quiroz; Marco Antonio Alvarado Cifuentes; Carlos Antonio Alvarado Cifuentes
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1596-1608

Abstract

In the present work, the design of a system to classify data is carried out, using the Scrum methodology. The validation was carried out by expert judgment, having favorable results in terms of different criteria such as; integrity, ease of use, innovation, and scalability. Regarding the development of the functional elements of the system, it was obtained; he developed the architecture of the system, the database, and the prototypes, among other points considered. From the implementation of the system, the equation of a classifying plane in three-dimensional space will be obtained, as well as the number of internal iterations that the algorithm develops, the estimated execution time, and the graph of the plane. This system is based on a recently introduced symmetric cone proximal multiplier algorithm to solve separable optimization problems, this algorithm made an application for classification-related support vector machines.
Cloud computing virtual learning environment: issues and challenges Aminah Rezqallah Malkawi; Muhamad Shahbani Abu Bakar; Zulkhairi Bin Md Dahlin
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1707-1712

Abstract

Cloud computing (CC) is a popular technology that has demonstrated its usefulness and effectiveness across industries and sectors worldwide. As a result, several educational institutions have recently integrated CC into their platforms and systems, including their virtual learning environment (VLE). In order to highlight the issues, challenges, and requirements to be taken into account before implementing CC technology within educational institutions, it is imperative to conduct a study to investigate the level of awareness, knowledge, and acceptance of the targeted users, who are educators, learners, and administrators of higher education institutions (HE). The result of the study highlighted some concerns facing users from 35 different institutions around the kingdom of Saudi Arabia. In addition, results highlighted the users' training, awareness, technology infrastructure, and cultural influences as factors to consider before adopting a sustainable and usable CC-VLE.
Optimal sensor location for adaptive control system in tropical smart greenhouse Folkes Eduard Laumal; Herry Suhardiyanto; Mohamad Solahudin; Slamet Widodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1449-1457

Abstract

The uniform control in greenhouse with technology capabilities is seemingly still difficult to be obtained due to the accuracy uncertainty of the data in certain locations. Considering this case, it is highly necessary to choose the right location for the sensor installation. This study aimed to determine sensor placement locations to support precision control activities, using an arch-type smart greenhouse measuring 8×24 m2 as the research location. Air temperature was calculated from 12 locations and analyzed for all possible combinations to designate the best sensor point according to the number of sensors. The analysis was conducted using the error-based method to ascertain the number and location of sensors that represent the smart greenhouse. The best location and number of sensors are identified with performance value under 10% and recommended for developing an adaptive control system.
A comparison of the performance of the ad hoc on-demand distance vector protocol in the urban and highway environment Ahmed Eskander Mezher; Atheer Akram AbdulRazzaq; Rajaa Kadhom Hasoun
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1509-1515

Abstract

In recent years, the vehicular ad hoc network (VANET) has received great attention, as it is involved in the design of the intelligent transportation system (ITS). The VANET network includes message flows from vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) where the network is propped by wireless communication technology, such as IEEE 1609 WAVE and IEEE 802.11P. The VANET network implementation faces challenges, and one of these challenges is the design of routing protocols that transfer reliable and efficient packets from vehicle to vehicle. In VANET, steering is a challenging task in the highway and urban environment. Therefore, this paper presents an assessment of ad hoc on-demand distance vector protocol (AODV) performance in the highway and urban environment and to study the effect of vehicle density on protocol performance. The AODV protocol was simulated by MATLAB. In this study, the performance of AODV protocol was evaluated through four measures, namely, packet delivery ratio (PDR), overhead, end-to-end (E2E) delay, and dropped packets. The study in our paper showed that the best performance of the AODV protocol is in an environment where vehicle speed and vehicle density are low.
Detection of occupancy status from internet connectivity for non-intrusive load monitoring Manjula Wickramathilaka; Md Pauzi Abdullah; Mohammad Yusri Hassan; Hayati Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1678-1688

Abstract

Non-intrusive load monitoring (NILM) methods are widely used for appliance level energy disaggregation in residential buildings. These methods mostly depend on electrical features, and they have not been much successful in applying for commercial buildings. However, recent research has indicated that the accuracy of existing NILM methods can be improved by associating with occupancy data. Therefore, in this paper a novel occupancy detection algorithm is proposed which can detect occupancy status of individuals using the connectivity of their information technology (IT) devices to the local area network of the building. The model is validated using data collected at a university building, with mean errors of 01:23 and 04:02 minutes for the detection of arrival and departure. The occupancy profiles developed by the proposed model can be used to disaggregate energy consumption in a commercial building to appliance and occupant level.

Page 3 of 7 | Total Record : 65

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