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 64 Documents
 3   4   5   6   7 
Search results for , issue "Vol 29, No 1: January 2023" : 64 Documents clear
Convolutional neural network-based crop disease detection model using transfer learning approach Segun Adebayo; Halleluyah Oluwatobi Aworinde; Akinwale O. Akinwunmi; Adebamiji Ayandiji; Awoniran Olalekan Monsir
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.pp365-374

Abstract

Crop diseases disrupt the crop's physiological constitution by affecting the crop's natural state. The physical recognition of the symptoms of the various diseases has largely been used to diagnose cassava infections. Every disease has a distinct set of symptoms that can be used to identify it. Early detection through physical identification, however, is quite difficult for a vast crop field. The use of electronic tools for illness identification then becomes necessary to promote early disease detection and control. Convolutional neural networks (CNN) were investigated in this study for the electronic identification and categorization of photographs of cassava leaves. For feature extraction and classification, the study used databases of cassava images and a deep convolutional neural network model. The methodology of this study retrained the models' current weights for visual geometry group (VGG-16), VGG-19, SqueezeNet, and MobileNet. Accuracy, loss, model complexity, and training time were all taken into consideration when evaluating how well the final layer of CNN models performed when trained on the new cassava image datasets.
Reclust: an efficient clustering algorithm for mixed data based on reclustering and cluster validation Amala Jayanthi Maria Soosai Arockiam; Elizabeth Shanthi Irudhayaraj
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.pp545-552

Abstract

Clustering is a significant approach in data mining, which seeks to find groups or clusters of data. Both numeric and categorical features are frequently used to define the data in real-world applications. Several different clustering algorithms are proposed for the numerical and categorical datasets. In clustering algorithms, the quality of clustering results is evaluated using cluster validation. This paper proposes an efficient clustering algorithm for mixed numerical and categorical data using re-clustering and cluster validation. Initially, the mixed dataset is clustered with four traditional clustering algorithms like expectation-maximization (EM), hierarchical cluster (HC), k-means (KM), and self-organizing map (SOM). These four algorithms are validated, and the best algorithm is selected for re-clustering. It is an iterative process for improving the quality of cluster results. The incorrectly clustered data is iteratively re-clustered and evaluated based on the cluster validation. The performance of the proposed clustering method is evaluated with a real-time dataset in terms of purity, normalized mutual information, rand index, precision, and recall. The experimental results have shown that the proposed reclust algorithm achieves better performance compared to other clustering algorithms.
Implementation of ethereum blockchain on transaction recording of white sugar supply chain data Ratna Ekawati; Yandra Arkeman; Suprihatin Suprihatin; Titi Candra Sunarti
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.pp396-403

Abstract

The complex supply chain system for the sugar agroindustry supply chain involves many actors, resulting in the asymmetry of information data. It still leads to a lack of data transparency. In the past, data traceability could not be made efficient at every stage, so the record data transaction was not real-time, less accurate, and inefficient coordination between actors. Blockchain is one of the technologies in the 4.0 era as a distributed ledger technology. It can be transparency, traceability, security, immutability, and decentralization. This study aims to design a white sugar agroindustry system based on blockchain technology using the SDLC waterfall stage public. Ethereum is a proof-of-work convention based on the Ropsten test-net on the Metamask wallet. The sugar supply chain system that has been successfully developed allows consumers to track the purchased sugar products based on the transaction hash code sent by the seller. The data listed is the location of the plantation, the quantity (quintal) and quality of sugarcane (percentage), and the purchase price. A web-based blockchain application could be used as a model by national sugar factories to help them make enough sugar food for themselves.
Dipole antenna with biconical and pyramidal horn design in radio frequency identification simulations Aaron Don M. Africa; Rica Rizabel M. Tagabuhin; Jan Jayson S. D. Tirados
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.pp181-189

Abstract

Radio frequency identification (RFID) systems are used in several applications. It is widely used in retail, corporations, and schools for several purposes such as inventory, identification, and cashless payments. The components of an RFID system include a tag and a reader. The RFID reader includes an RF module that transmits and receives signals. While the RFID tag transmits embedded signals, which is typically some form of identification. The tag is a passive component powered by the reader. The two components make use of antennas to communicate the signals with each other. The design of the antenna is an important factor to consider in the production of the RFID. The size of the antenna must be small enough to provide convenience and the gain must be strong enough to effectively transmit and receive signals between the two components. In this paper, an antenna for an RFID tag is designed using MATLAB software. The antenna to be designed must be cost-efficient and be able to radiate an acceptable gain. This research creates a dipole antenna with biconical and pyramidal horn design in RFID simulations.
Comparison of ensemble hybrid sampling with bagging and boosting machine learning approach for imbalanced data Nur Hanisah Abdul Malek; Wan Fairos Wan Yaacob; Yap Bee Wah; Syerina Azlin Md Nasir; Norshahida Shaadan; Sapto Wahyu Indratno
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.pp598-608

Abstract

Training an imbalanced dataset can cause classifiers to overfit the majority class and increase the possibility of information loss for the minority class. Moreover, accuracy may not give a clear picture of the classifier’s performance. This paper utilized decision tree (DT), support vector machine (SVM), artificial neural networks (ANN), K-nearest neighbors (KNN) and Naïve Bayes (NB) besides ensemble models like random forest (RF) and gradient boosting (GB), which use bagging and boosting methods, three sampling approaches and seven performance metrics to investigate the effect of class imbalance on water quality data. Based on the results, the best model was gradient boosting without resampling for almost all metrics except balanced accuracy, sensitivity and area under the curve (AUC), followed by random forest model without resampling in term of specificity, precision and AUC. However, in term of balanced accuracy and sensitivity, the highest performance was achieved by random forest with a random under-sampling dataset. Focusing on each performance metric separately, the results showed that for specificity and precision, it is better not to preprocess all the ensemble classifiers. Nevertheless, the results for balanced accuracy and sensitivity showed improvement for both ensemble classifiers when using all the resampled dataset.
Nonlinear backstepping control of a partially shaded photovoltaic storage system Sabri Khadija; El Maguiri Ouadia; Farchi Abdelmajid
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.pp225-237

Abstract

Many power converter architectures and control approaches, both traditional and unconventional, have been developed, investigated, and adjusted to handle the challenge of tracking the maximum power points of a partially shaded photovoltaic (PV) system, which fluctuates with meteorological conditions (radiation and temperature). A DC-DC converter was used as the power conditioning unit to determine the system’s maximum efficiency. In this research, we focus on developing a nonlinear controller for a DC-DC converter to track the overall maximum power point in a PV storage system under partial shading situations. This study presents a combination of two MPP search algorithms with a backstepping controller. The particle swarm optimization (PSO) and variable step Perturb and Observe (P&O)with global scan (VSP&O/GS) algorithms supply the PV output reference voltage to the backstepping controller in order to recover the maximum power from photovoltaic (PV) systems. The simulation results of the methods compared to the proposed maximum power point (MPPT) algorithm are simulated and examined in the MATLAB/Simulink environment under non-uniform irradiation conditions. To demonstrate the performance and limits of each approach in tracking the maximum power point.
A discrete salp swarm algorithm with weights and Lévy flights: application for Parkinson’s disease detection Nitesh M. Sureja; Pratik N. Patel; Hemant Patel; Chetan J. Shingadiya
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.pp472-480

Abstract

A new hybrid algorithm named discrete salp swarm algorithm that integrates effectiveness of weights, Lévy flights, and an excellent classifier, support vector machine (SVM), has been proposed to predict Parkinson's disease. In the proposed algorithm, salp swarm algorithm (SSA) is used as a feature selection tool, which targets to reduce the noise in features of the speech PD dataset to improve the SVM classifier's prediction accuracy. The efficacy and usefulness of the proposed discrete salp swarm algorithm with Lévy flights have been meticulously assessed against the speech PD dataset in terms of G-mean, accuracy, F-measure, specificity, sensitivity, and precision measures. DWLSSA has achieved values of the measures, 97.76%, 98.75%, 98.77%, 97.37%, 98.15%, and 99.39% respectively. Comparison of DWLSSA with other nature inspired algorithms applied to predict Parkinson’s shows that the proposed DWLSSA performs better. It can be also said that DWLSSA can be an alternative for solving the NP-hard problems.
Object detection on robosoccer environment using convolution neural network Diana Steffi; Shilpa Mehta; Venkatesh Venkatesh
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.pp286-294

Abstract

Robots with autonomous capabilities depend on vision capabilities to detect and interact with objects and their environment. In the field of robotic research, one of the focus areas is the robosoccer platform that is being used to implement and test new ideas and findings on computer vision and decision making. In this article, an efficient real-time object detection algorithm is employed in a robosoccer simulation environment by deploying a convolution neural network and Kalman filter based tracking algorithms. This study's objective is to classify nao, ball, and the goalpost as well as to validate nao and ball tracking without human intervention from initial frame to last frame. In comparison with the existing methods, the proposed method is robust and fast in identifying three classes namely nao, ball, and goalpost with a speed of 1.67 FPS and a mAP of 95.18%. By implementing this approach, soccer playing robots can make appropriate decisions during game play.
Algebraic fields and rings as a digital signal processing tool Dinara Kutlimuratovna Matrassulova; Yelizaveta Sergeevna Vitulyova; Sergey Vladimirovich Konshin; Ibragim Esenovich Suleimenov
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.pp206-216

Abstract

It is shown that algebraic fields and rings can become a very promising tool for digital signal processing. This is mainly due to the fact that any digital signals change in a finite range of amplitudes and, therefore, there are only a finite set of levels that can correspond to the amplitudes of a signal reduced to a discrete form. This allows you to establish a one-to-one correspondence between the set of levels and such algebraic structures as fields, rings, etc. This means that a function that takes values in any of the algebraic structures containing a finite set of elements can serve as a model of a signal reduced to a discrete form. A special case of such a signal model are functions that take values in Galois fields. It is shown that, along with Galois fields, in certain cases, algebraic rings contain zero divisors can be used to construct signal models. This representation is convenient because in this case it becomes possible to independently operate with the digits of the number that enumerates the signal levels. A simple and intuitive method for constructing rings is proposed, based on an analogy with the method of algebraic extensions.
Evaluation of the functionality of the virtual platform in the teaching process: analysis based on the usability factor Omar Chamorro-Atalaya; Dora Arce-Santillan; Guillermo Morales-Romero; Beatriz Caycho-Salas; Teresa Guía-Altamirano; César León-Velarde; Risley Rengifo-Tello
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.pp583-590

Abstract

The use of virtual platforms has been increasing exponentially during the context of distance education, however, there are still limitations to innovate in pedagogical proposals. This can hinder the assurance of student learning, either due to the little planning that occurred in its incorporation, the little knowledge of teachers and students in the educational use or the lack of use of the functionalities that they have incorporated for communication. The purpose of the research is to evaluate the operability of the virtual platform in the teaching-learning process through analysis based on the usability factor, the results will allow us to continue improving the tools linked to distance higher education. At the development of the investigation, a reliability value of 0.985 was obtained by means of Cronbach's Alpha. It was found as findings that 73.8% perceive an improvement in communication and in the exchange of information. Regarding the usability factor, 73.9% fully agree with the information available on the virtual platform and its accessibility. From what was determined, it is concluded that 65.98% of students consider that the functionality of the virtual platform with respect to the usability factor positively influences the teaching-learning process.

Page 5 of 7 | Total Record : 64

 3   4   5   6   7 

Filter by Year

2023 2023


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