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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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Kenaf plant pest and disease detection using faster regional based convolutional neural network Alfita Rakhmandasari; Wayan Firdaus Mahmudy; Titiek Yulianti
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp198-207

Abstract

Kenaf plant is a fibre plant whose stem bark is taken to be used as raw material for making geo-textile, particleboard, pulp, fiber drain, fiber board, and paper. The presence of plant pests and diseases that attack causes crop production to decrease. The detection of pests and diseases by farmers may be a challenging task. The detection can be done using artificial intelligence-based method. Convolutional neural networks (CNNs) are one of the most popular neural network architectures and have been successfully implemented for image classification. However, the CNN method is still considered a long time in the process, so this method was developed into namely faster regional based convolution neural network (RCNN). As the selection of the input features largely determines the accuracy of the results, a pre-processing procedure is developed to transform the kenaf plant image into input features of faster RCNN. A computational experiment proves that the faster RCNN has a very short computation time by completing 10000 iterations in 3 hours compared to convolutional neural network (CNN) completing 100 iterations at the same time. Furthermore, Faster RCNN gets 77.50% detection accuracy and bounding box accuracy 96.74% while CNN gets 72.96% detection accuracy at 400 epochs. The results also prove that the selection of input features and its pre-processing procedure could produce a high accuracy of detection. 
Advanced UI test automation (AUTA) for BIOS validation using OpenCV and OCR Eissa Abdullah Awadh Mohammed; Muslim Mustapa; Hasliza Rahim; Mohd Natashah Norizan
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1350-1356

Abstract

Basic input output system (BIOS) validation is performed on both graphical user interface (GUI) and command-line interface (CLI) by a test engineer. Keyboard and mouse are used to insert test cases commands into system under test (SUT). Test engineer monitors test cases progress on a monitor for validation. This method is time-consuming and relatively more expensive than automation. In this project we designed an independent automation system that able to mimic human interaction in BIOS validation. The approach can be divided into two main parts. The first part is the input device to enter commands into SUT and the second part is the advanced image recognizer. The keyboard and mouse emulator is used as an input device to reproduce test commands and send them to an SUT. The image analyzer algorithm is developed using OpenCV and optical character recognizer (OCR) tools to help automate some test challenges. Our result shows that advanced user interface (UI) test automation (AUTA) can perform a 125 test cases within 5 hours compared to 48 hours for a human to complete the job.
An improved Kohonen self-organizing map clustering algorithm for high-dimensional data sets Momotaz Begum; Bimal Chandra Das; Md. Zakir Hossain; Antu Saha; Khaleda Akther Papry
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp600-610

Abstract

Manipulating high-dimensional data is a major research challenge in the field of computer science in recent years. To classify this data, a lot of clustering algorithms have already been proposed. Kohonen self-organizing map (KSOM) is one of them. However, this algorithm has some drawbacks like overlapping clusters and non-linear separability problems. Therefore, in this paper, we propose an improved KSOM (I-KSOM) to reduce the problems that measures distances among objects using EISEN Cosine correlation formula. So far as we know, no previous work has used EISEN Cosine correlation distance measurements to classify high-dimensional data sets. To the robustness of the proposed KSOM, we carry out the experiments on several popular datasets like Iris, Seeds, Glass, Vertebral column, and Wisconsin breast cancer data sets. Our proposed algorithm shows better result compared to the existing original KSOM and another modified KSOM in terms of predictive performance with topographic and quantization error.
Effect of electrical discharge on the properties of natural esters insulating fluids Imran Sutan Chairul; Sharin Ab Ghani; Nur Hakimah Ab Aziz; Mohd Shahril Ahmad Khiar; Muhammad Syahrani Johal; Mohd Aizzat Azmi
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1281-1288

Abstract

Vegetable oils have been an alternative to mineral oil for oil-immersed transformers due to concern on less flammable, environmental-friendly, biodegradable, and sustainable resources of petroleum-based insulating oil. This paper presents the effect of electrical discharges (200 up to 1000 discharges) under 50 Hz inhomogeneous electric field on the properties (acidity, water content, and breakdown voltage) of two varieties of vegetable based insulating oils; i) natural ester (NE) and ii) low viscosity insulating fluids derived from a natural ester (NELV). Results show the water content, acidity and breakdown voltage of NE fluctuate due to applied discharges, while NELV display insignificant changes. Hence, results indicate that the low viscosity insulating fluids derived from natural ester tend to maintain their properties compared to natural ester.
Performance evaluation of SIFT against common image deformations on iban plaited mat motif images Silvia Joseph; Irwandi Hipiny; Hamimah Ujir; Sarah Flora Samson Juan; Jacey-Lynn Minoi
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1470-1477

Abstract

Decorative plaited mat is one of the many examples of rich plait work often seen on Borneo handicraft products. The plaited mats are decorated with simple and complex motif designs; each has its own special meaning and taboos. The motif designs are used as a reflection of environment and the traditional beliefs in the Iban community. In line with efforts from UNESCO’s and Sarawak Government’s, digitization, and the use of IR4.0 technologies to preserve and promote this cultural heritage is encouraged. Towards this end goal, we present a novel image dataset containing 10 Iban plaited mat motif classes. The plaited mat motifs are made of diagonal and symmetrical shapes, as well as geometric and non-geometric patterns. Classification’s accuracy using scale-invariant feature transform (SIFT) features was evaluated against 6 common image deformations: zoom+rotation, viewpoint, image blur, JPEG compression, scale and illumination, across multiple threshold values. Varying degrees of each deformation were applied to a digitally cleaned (and cropped) image of each mat motif class. We used RANSAC to remove outliers from the noisy SIFT matching result. The optimal threshold value is 2.0e-2 with a reported 100.0% matching accuracy for the scale change and zoom+rotation set.
Portable gas leak detection system using IoT and off-the shelf sensor node Marwan Ihsan Shukur Al-Jemeli; Maythem Kamal Abbas Al-Adilee
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp491-499

Abstract

In companies that use toxic gases in vast amounts for a range of procedures, there are a host of high-risk concerns to address. People will not be able to track or control the emission of these gases on a routine basis until it becomes harmful. Sensors are expected to actively detect leaks and alert users to any potential hazards. Gas leakage may occur at multiple locations within a single installation. As a result, sensors are implanted as close to the suspected leak site as possible, enabling them to track leakage and relay signals to a base station that is situated far away. Many sensor values are received and analyzed using a microcontroller. The generated data is encoded in the wireless module and sent to the base through the internet of things link, where it is decoded and viewed by another microcontroller. When leaks are detected, the device sends an audio and visual alert, and since the detection period is very limited due to high-speed processing, leakage situations are brought under control with minimal or no effect. Using the new IoT technology and tracking from anywhere on the network, this project offers a cost-effective and reliable solution for mitigating leakage risk.
Dual-band doherty power amplifier with improved reactance compensation Li M. Yu; Narendra K. Aridas; Tarik A. Latef
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1550-1556

Abstract

In brief, a dual-band doherty power amplifier employing reactance compensation with gallium nitride high-electron-mobility transistor technology is discussed. This design is developed for long-term evolution (LTE) frequency operation, particularly for the application of two-way radio to improve the efficiency at the back-off point from saturation output power for selected dual frequencies in the LTE bandwidth. Measurements show that the prototype board has enhanced performance at the desired frequencies, namely a saturation output power of 40.5 dBm, and 6 dB back-off efficiencies of 43% and 47%, which exhibit a gain of approximately 10 dB at 0.8 GHz and 2.1 GHz, respectively.
Raga classification based on pitch co-occurrence based features Vibhavari Rajadnya; Kalyani R. Joshi
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp157-166

Abstract

Analysis and classification of raga is the need of time especially in music industry. With the presence of abundance of multimedia data on internet, it is imperative to develop appropriate tools to classify ragas. In this work, an attempt has been made to use occurrence pattern of pitch based svara (note) for classification. Sequence of notes is an important cue in the raga classification. Pitch based svara (note) profile is formed. This pattern presents in the signal along with its statistical distribution can be characterized using co-occurrence matrix. Proposed note co-occurrence matrix summarizes this aspect. This matrix captures both tonal and temporal aspects of melody. Ragas differ in terms of distribution of spectral power. K-nearest neighbor (KNN) has been used as the classifier. Publicly available database consisting of 300 recordings of 30 Hindustani ragas consisting of 130 hours of audio recordings stored as 160 kbps mp3 fileswhich is part of CompMusic project is used. Leave one out validation strategy is used to evaluate the performance. Experimental result indicates the effectiveness of the proposed scheme which is giving accuracy of 93.7%.
A computational experimental of noise suppressing technique stand on hard decision threshold dissimilarity Vorapoj Patanavijit; Kornkamol Thakulsukanant
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp144-156

Abstract

Due to the extreme insistence for digital image processing, plentiful modern noise suppressing techniques are embodied of dissimilarity process and suppressing process. One of the extreme capability dissimilarity is hard decision threshold (HDT) dissimilarity, which has been recently declared in 2012, for suppressing the impulsive noisy photographs thus the computer experimental statement attempts to investigate the capability of the noise suppressing technique that is stand on HDT dissimilarity for the processed photographs, which are corrupted by fixed-intensity impulse noise (FIIN). This paper proposes the noise suppressing technique stand on HDT dissimilarity for FIIN. There are 3 primary contributions of this paper. The first contribution is the statistical average of the HDT dissimilarity of noise-free elements, which are computed from plentiful ground-truth photographs by varying window size for the best HDT window size. The second contribution is the statistical average of the HDT dissimilarity of corrupted elements, which are computed from plentiful corrupted photographs by varying outlier density for the best HDT window size. The final contribution is the statistical interrelation of the capability of the noise suppressing technique and hard consistent of HDT dissimilarity are investigated by varying the outlier denseness for the best HDT hard consistence.
AQUACISION: a multiparameter aquaculture water quality ester and decision support system Mark Anthony A. Lazo; Louise Mark Kit S. Geronimo; Lester John T. Comilang; Kenneth John B. Cayme; Jay M. Ventura; Ertie C. Abana
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp530-537

Abstract

The paper presents a multiparameter aquaculture water quality tester with a decision support system. A device was developed to aid aquaculture farmers in monitoring water quality parameters and maintaining or achieving optimal levels by suggesting ways on how a farmer can respond to such measurements. The AQUACISION device measures six different water quality parameters; temperature, practical salinity, pH level, total dissolved solid (TDS), oxidation-reduction potential (ORP), and algae density. Measurements were sent to the AQUACISION application where they were processed to determine the course of action that was best to maintain or achieve optimal levels using fuzzy rules. Based on the comparative result, the AQUACISION was accurate in measuring temperature, practical salinity, pH level, TDS, and ORP during the actual testing. The application also received an excellent rating on the ISO/IEC 25010 software quality model standard

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