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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
 603   604   605   606   607 
Pre-trained deep learning models in automatic COVID-19 diagnosis Ahmed Wasif Reza; Md Mahamudul Hasan; Nazla Nowrin; Mir Moynuddin Ahmed Shibly
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1540-1547

Abstract

Coronavirus Disease (COVID-19) is a devastating pandemic in the history of mankind. It is a highly contagious flu that can spread from human to human without revealing any symptoms. For being so contagious, detecting patients with it and isolating them has become the primary concern for healthcare professionals. This study presented an alternative way to identify COVID-19 patients by doing an automatic examination of chest X-rays of the patients. To develop such an efficient system, six pre-trained deep learning models were used. Those models were: VGG16, InceptionV3, Xception, DenseNet201, InceptionResNetV2, and EfficientNetB4. Those models were developed on two open-source datasets that have chest X-rays of patients diagnosed with COVID-19. Among the models, EfficientNetB4 achieved better performances on both datasets with 96% and 97% of accuracies. The empirical results were also exemplary. This type of automated system can help us fight this dangerous virus outbreak.
Integrated NIR-HE based SPOT-5 image enhancement method for features preservation and edge detection Farizuwana Akma Zulkifle; Rohayanti Hassan; Mohammad Nazir Ahmad; Shahreen Kasim; Tole Sutikno; Shahliza Abd Halim
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1499-1514

Abstract

Recently, many researchers have directed their attention to methods of predicting shorelines by the use of multispectral images. Thus, a simple and optimised method using image enhancements is proposed to improve the low contrast of the Satellite pour l'Observation de la Terre-5 (SPOT-5) images in the detection of shorelines. The near-infrared (NIR) channel is important in this study to ensure the contrast of the vegetated area and sea classification, due to the high reflectance of leaves in the near infrared wavelength region. This study used five scenes of interest to show the different results in shoreline detection. The results demonstrated that the proposed method performed in an enhanced manner as compared to current methods when dealing with the low contrast ratio of SPOT-5 images. As a result, by utilising the near-infrared histogram equalization (NIR-HE), the contrast of all datasets was efficiently restored, producing a higher efficiency in edge detection, and achieving higher overall accuracy. The improved filtering method showed significantly better shoreline detection results than the other filter methods. It was concluded that this method would be useful for detecting and monitoring the shoreline edge in Tanjung Piai.
Web-based document certification system with advanced encryption standard digital signature Henny Indriyawati; Titin Winarti; Vensy Vydia
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp516-521

Abstract

Web-based degree document certification system with a digital signature in Semarang University has a purpose to support academic to do online document certification through a system. The main problem which occurs in academic administration is a long document certification process that causes an ineffective and inefficient certification process. To solve the problem, a system that can encrypt a document for better security is required. This system is built with the advanced encryption standard algorithm with a 128-bit sized key to encrypt confidential information inside the document. During the encryption process, this algorithm operates using 4x4 bit array blocks and passing many encryption processes for at least 10 (ten) times. The application is analyzed with object-oriented analysis and modeled with Unified modeling language. The result of this research is a system which can secure document with AES algorithm with a 256-bit sized key. The security element in this algorithm will make easier to identify the owner of the document. The secured document is easily accessible through PHP-based web or available QR code. When decrypting the document, the application will activate the camera function and decrypt the information document.
High speed pulse generators with electro-optic modulators based on different bit sequence for the digital fiber optic communication links Mahmoud M. A. Eid; Ashraf S. Seliem; Ahmed Nabih Zaki Rashed; Abd El-Naser A. Mohammed; Mohamed Yassin Ali; Shaimaa S. Abaza
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp957-967

Abstract

The paper outlines the simulation of various pulse generators for the enhancement of optical fiber access transmission networks within flow rate of 10 Gbps and transmission range of 100 km. The pulse generators are gaussian, hyperbolic secant, triangle, sine, raised cosine in the transmission stage. Proposed pulse generators are mixed with both electro-absorption modulator (EAM) and mach-zehnder modulator (MZM) for efficient transmission. We have compared the max.  the quality factor with using proposed pulse generators against nonreturn to zero (NRZ) return to zero (RZ) pulse generators in the previous research works for different bit sequences. The signal power amplitude is tested for both optical fiber and PIN photodetector optical time-domain visualizer and RF spectrum analyzer by using in the optimum cases for different bit sequence. It is observed that proposed pulse generators/EAM have presented an efficient increase in Q-factor value compared with proposed pulse generators/MZM for different bit sequences.
Efficacy of chili plant diseases classification using deep learning: a preliminary study Rozlan, Suhana; Hanafi, Marsyita
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1442-1449

Abstract

Plant disease classification using deep learning techniques is a popular research area due to the numerous opportunities for introducing advance and robust classifiers. Nevertheless, classifying chilli plant diseases accurately from images under uncontrolled environment and various imaging conditions remains unsolved due to the lack of chilli disease image datasets. In this study, the efficacy of three high-performance deep learning algorithms, namely VGG16, InceptionV3, and EfficientNetB0, in classifying three types of chilli leaves diseases, namely upward curling, mosaic/mottling, and the bacterial spot, is demonstrated. These methods are popularly used for other plant disease classifications due to their effectiveness. The experiments were performed on the 3,000 chilli plant disease images collected from three different field environments in Selangor, Malaysia. The images were captured with a complex background and various illuminations, angles, and distances to reflect the real-life scenarios. The complexity of the collected images was created based on the taxonomic information of chilli leaves diseases and the unavailability of chilli disease images under various imaging conditions in the publicly available plant disease databases. Experimented using appropriate specifications, the models demonstrated outstanding performance with more than 95% accuracy with the highest accuracy of 98.83% by InceptionV3.
Design of circular inductive pad couple with magnetic flux density analysis for wireless power transfer in EV Syasya Azra Zaini; Mohd Shahrin Abu Hanifah; Siti Hajar Yusoff; Nadia Nazieha Nanda; Ahmed Samir Badawi
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp132-139

Abstract

As the population grows, people will consume more natural resources. This issue will lead to a low petrol supply for all land transportation, especially supplies for car consumption. Therefore, the electric vehicle (EV) has been introduced to overcome this issue. Currently, wired charging of EVs has been implemented in most of the developed country, including Malaysia. However, some drawbacks have been found from this technology. Therefore, wireless charging comes into the picture to solve this issue. Charging pad on the road and at the car are required for both wired and wireless charging. Various designs of charging pad are available. However, this paper will only focus on the circular design. There is many software that can be used to design the coil pad. Each software has a different procedure and steps to design the coil pad. In this paper, JMAG Designer software will be used to design the circular coil pad. Then, three coil pair were simulated using JMAG Designer to investigate the magnetic flux density between primary and secondary coil when varying the misalignment of 0 cm, 4 cm and 8 cm. From the simulation, there is no specific trend in the relationship between magnetic flux density and misalignment.
Coverage enhancements of vehicles users using mobile stations at 5G cellular networks Jaafar A. Aldhaibani; Mohanad S. Alkhazraji; Hasanain Lafta Mohammed; Abid Yaya
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp388-395

Abstract

High mobility requirements are one of the challenges face fifth-generation wireless (5G) cellular networks by providing acceptable wireless services to users traveling at speed up to 350 km/h. This paper presents a new scenario to increase the bit rate and coverage for passengers that use the vehicles for traveling through the installation a mobile station (MS) on these vehicles to provide a high-quality service to users. Based on signal to noise ratio (SNR’s) mathematical derivation and the outage probability of the user link, the proposed system is evaluated. Numerical results indicate an enhancement for users who received signal strength (RSS) from (-72 to -55) dBm and (15 to 38) Mbps in bit rate. Moreover, their number of users increased by proposed system adoption.
Algorithm for extracting product feature from e-commerce comment Chanida Kaewphet; Nawaporn Wisitpongpun
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp1199-1207

Abstract

Reviews of e-commerce play an important role in online purchasing decisions. Consumers are likely to read reviews and comments on products from other consumers. In addition to those opinions that reflect consumers' trust in products, it also provides each product's distinctive properties. Today, there are many online reviews, resulting in enormous comments and suggestions. However, as fully reading reviews is quite difficult, this article presents 3 algorithms for automatic extraction of product features hidden in e-commerce reviews: a traditional frequency-based product feature extraction (F-PFE), syntax analyzer system (SAS), and the hybrid approach called the frequency and syntax-based product feature extraction (FaS-PFE). The proposed algorithms were tested against 4 different types of products: shampoo, skincare, mobile phone, and tablet, using reviews from amazon.com. Based on the product review used in this study, it was found that the SAS can help improve the performance in terms of precision by 15% when compared with the traditional F-PEE approach. When considering both the word frequency and syntax, FaS-PFE clearly outperforms the other two approaches with 94.00% precision and 95.13% recall.
Face Recognition with Frame size reduction and DCT compression using PCA algorithm Padmaja vijaykumar; Jeevan K Mani
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp168-178

Abstract

Face recognition has become a very important study of research because it has a variety of applications in research field such as human computer interaction, pattern recognition (PR). A successful face recognition procedure, be it mathematical or numerical, depends on the particular choice of the features used by the classifier. Feature selection in pattern recognition consists of the derivation of salient features present in the raw input data in order to reduce the amount of data used for classification. For the successful face recognition, the database images must have sufficient information so that when presented with the probe image, the recognition must be possible. Majority of times, there is always excess information present in the database images, leads higher storage, hence optimum size of the images needs to be stored in the database for good performance, are compressed with reduction in frame size and then compressed with that of the DCT. 
Reducing image search time by improved BOVW with wavelet decomposition Mohammed El Amin Kourtiche; Mohammed Beladgham; Abdelmalik Taleb-Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1201-1208

Abstract

In the last decade, the bag of visual words (BOVW) has been used widely in image classification, image retrieval and has significantly improved the performance of CBIR system. In this paper we propose a new method to enhance BOVW using features obtained from wavelet decomposition in order to reduce computational costs in vocabulary construction and training time. We apply several level of wavelet decompositions and evaluate their impact on accuracy of the BOVW. We apply our method on MURA-v1.1 dataset and the experiments results confirm the performance of our approach.

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