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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
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Performance Analysis of Fiber Attenuation in Passive Optical Networks Augustus E. Ibhaze; Adekunle O. Gbadebo; Akinwumi A. Amusan; Samuel N. John
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4919

Abstract

The introduction of Fiber Optics cables in broadband Internet distribution has been a game changer in bulk capacity delivery, speed, reliability and penetration. However, the uncurbed incessant existence of cuts and failures have threatened the growth of Internet connectivity as a whole. In this work, the impact of fiber cuts is investigated using a hybrid approach, encompassing both real-world data from a live GPON network and simulations using OptiSystem 12 for FTTH GPON scenarios. Fiber cuts and failures are emulated by introducing varying attenuation levels in the simulated network's feeder cable section within OptiSystem 12, while in the live GPON network, the attenuation is induced by introducing wrap bends in the last-mile patch cord. The findings reveal a consistent pattern in both simulated and live data for both downstream and upstream traffic scenarios. As attenuation levels increased, there was a corresponding decline in Q-factor, Eye Height, and optical power, coupled with a concurrent rise in the minimum BER. Thus, in the most severe scenario, fiber cuts can result in service degradation and eventual service outage. To mitigate this issue, the implementation of a type�B PON protection system with a wireless auto-failover technique is proposed. Adoption and deployment of the proposed technique and deliberate maintenance measures alongside thorough supervision are suggested to be possible solutions to fiber cuts in metropolitan parlance.
Efficient Medical Image Compression Based on Wavelet Transform and Modified Gray Wolf Optimization Shahla Sohail; S Thenmozhi; Swetha Priyanka Jannu; R. Gayathiri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4329

Abstract

The use of medical images in diagnostic procedures is increasing, leadning to a significant rise in the memory and bandwidth requirements for preserving and transmitting these images. To address this issue, image compression techniques have garnered significant attention. These techniques are capable of reducing the data size necessary to represent an image, allowing for more efficient utilization of storage space and communication bandwidth by eliminating unnecessary information. Numerous research directions have focused on compressing medical images, but past approaches have been time-consuming and risked information loss. To trounce these limitations, this paper introduces an effiective method for reducing the size of medical images in telemedicine applications. The method utilizes Integer Wavelet Transform (IWT) and sophisticated algorithm. Primarily, input images undergo pre-processing with a circular median filter to eliminate noise and improve image quality. Subsequently, the pre-processed images are divided into multiple sub bands using IWT.Then, these sub bands are furhter divided into n X n non-overlapping matrices, and optimal coefficients are chosen by employing a modified grey wolf optimizer algorithm. Finally, the selected coefficients are encoded using Huffman coding for transmission. During decompression, the reverse process of image compression is applied. The introduced method is tested on various medical images, and the findings demonstrate its superior performance compared to previous methods, generating visually similar images with a smaller data size.
Hand Gestures Replicating Robot Arm based on MediaPipe Muneera Altayeb
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4491

Abstract

A robotic arm is any variety of programmable mechanical devices designed to operate items like a human arm and is one of the most beneficial innovations of the 20th century, quickly becoming a cornerstone of many industries. It can perform a variety of tasks and duties that may be time-consuming, difficult, or dangerous to humans. The gesture-based control interface offers many opportunities for more natural, configurable, and easy human-machine interaction. It can expand the capabilities of the GUI and command line interfaces that we use today with the mouse and keyboard. This work proposed changing the concept of remote controls for operating a hand-operated robotic arm to get rid of buttons and joysticks by replacing them with a more intuitive approach to controlling a robotic arm via the hand gestures of the user. The proposed system performs vision-based hand gesture recognition and a robot arm that can replicate the user's hand gestures using image processing. The system detects and recognizes hand gestures using Python and sends a command to the microcontroller which is the Arduino board connected to the robot arm to replicate the recognized gesture. Five servo motors are connected to the Arduino Nano to control the fingers of the robot arm; These servos are related to the robot arm prototype. It is worth noting that this system was able to repeat the user's hand gestures with an accuracy of up to 96%.
Factors Influencing the Adoption of Cloud-based Village Information System: A Technology-Organization-Environment Framework and AHP–TOPSIS Integrated Model Theresiawati Theresiawati; Tjahjanto Tjahjanto; Yuni Widiastiwi; Hamonangan Kinantan Prabu; Bambang Tri Wahyono; Wan Nor Shuhadah Wan Nik
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4516

Abstract

Cloud-based service is a key area for growth in Indonesia, but there are still very few villages that have adopted a village information system based on cloud computing. This study investigates the factors influencing OpenSID adoption in cloud computing. The research was informed by the Technological Organizational Environmental (TOE) and combined two multi-criteria decision analysis methods, namely, AHP and TOPSIS to analyze the acceptance of cloud computing-based village information systems, the driving factors for adoption, and the selection of forms of OpenSID. The research focuses on the analysis of four dimensions namely organization, trust, innovation, and vendor. The sub-dimensions of each dimension include the organization (the technological readiness of actors, top management support, and firm size), Trust (security and privacy factors), innovation (compatibility, complexity, trialability, and relative advantage factors), and Vendor (vendor reputation, perceived price, and external support factors). Primary data was collected using a questionnaire and semi-structured interviews with respondents from the village government apparatus in Indramayu.  The results of the study showed an open-source cloud-based village information system is the most suitable alternative solution for government at the village level in Indramayu, West Java Province.  The results highlighted that the enablers that are critical for cloud adoption include Technology readiness, trust, technological innovation, and vendor. The barriers that are hindering cloud adoption are infrastructure readiness, understanding the use of cloud computing technology, low technical skills and knowledge, data integration issues, and data security. This research is a reference for developing a village information system based on cloud computing.
AIoTST-CR : AIoT Based Soil Testing and Crop Recommendation to Improve Yield Shradha Joshi-Bag; Archana Vyas
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4858

Abstract

Agriculture is a backbone of any country. Farmers need to test the soil fertility and nutrients present in the soil for proper growth of the crops. In traditional system, the farmers collect soil sample and submit to soil testing labs for testing the soil nutrients and get the soil test reports manually. Farmers based on his experience and the season; decide which crop to be taken in the farm. Based on soil testing reports farmers decide which fertilizers required for the proper growth of the crop. This process is time consuming and human efforts are required and hence crop yield is affected. The recent technologies in cloud storage, wireless sensors,  and AI based algorithms are very instrumental in decision making process of crop growth life cycle. Farmers can make use of mechanical automation tools for seeding, watering, supplying fertilizers, crop cutting etc. for proper growth of the crop. However, to observe the crop growth during the entire life cycle of crop farmer has to take lot of efforts to check need of water, any problem of disease to the crop, any specific fertilizers required or not and whether there is a need of harvesting. A proper decision support system is needed for helping the farmers in all such activities. Such support can be provided to a farmer so that he will be well updated about the growth of his crop in the farm. To reduce the human efforts and improve the crop yield, Artificial Intelligence and IOT based soil testing and Crop Recommendation system (AIoTST-CR) is designed and developed. AIoT based handheld soil testing system has pH, Nitrogen, Phosphorous, Potassium and Soil moisture sensing capability. A mobile application is developed to fetch the sensed data from AIoT system. A historical data is inputted to give training to ML models. Machine learning algorithm is used to predict and recommend the crop to be taken. The results show AIoTST-CR which is AIoT based soil testing and crop recommendation system provides effortless and accurate recommendations of crop. Our findings indicate that AIoT based system provides high accuracy, which outperforms existing commonly, used machine learning based crop recommendation systems.
Malayalam Handwritten Character Recognition using CNN Architecture Pranav P Nair; Ajay James; Philomina Simon; Bhagyasree P V
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4829

Abstract

The process of encoding an input text image into a machine-readable format is called optical character recognition (OCR). The difference in characteristics of each language makes it difficult to develop a universal method that will have high accuracy for all languages. A method that produces good results for one language may not necessarily produce the same results for another language. OCR for printed characters is easier than handwritten characters because of the uniformity that exists in printed characters. While conventional methods find it hard to improve the existing methods, Convolutional Neural Networks (CNN) has shown drastic improvement in classification and recognition of other languages. However, there is no OCR model using CNN for Malayalam characters. Our proposed system uses a new CNN architecture for feature extraction and softmax layer for classification of characters. This eliminates manual designing of features that is used in the conventional methods. P-ARTS Kayyezhuthu dataset is used for training the CNN and an accuracy of 99.75% is obtained for the testing dataset meanwhile a collection of 40 real time input images yielded an accuracy of 95%.
Acute Lymphoblastic Leukemia Blood Cells Prediction Using Deep Learning & Transfer Learning Technique Omkar Subhash Ghongade; S Kiran Sai Reddy; Yaswanth Chowdary Gavini; Srilatha Tokala; Murali Krishna Enduri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4855

Abstract

White blood cells called lymphocytes are the target of the blood malignancy known as acute lymphoblastic leukemia (ALL). In the domain of medical image analysis, deep learning and transfer learning methods have recently showcased significant promise, particularly in tasks such as identifying and categorizing various types of cancer. Using microscopic pictures, we suggest a deep learning and transfer learning-based method in this research work for predicting ALL blood cells. We use a pre-trained convolutional neural network (CNN) model to extract pertinent features from the microscopic images of blood cells during the feature extraction step. To accurately categorize the blood cells into leukemia and non- leukemia classes, a classification model is built using a transfer learning technique employing the collected features. We use a publicly accessible collection of microscopic blood cell pictures, which contains samples from both leukemia and non-leukemia, to assess the suggested method. Our experimental findings show that the suggested method successfully predicts ALL blood cells with high accuracy. The method enhances early ALL detection and diagnosis, which may result in better patient treatment outcomes. Future research will concentrate on larger and more varied datasets and investigate the viability of integrating it into clinical processes for real-time ALL prediction.
Examination on the Denoising Methods for Electrical and Acoustic Emission Partial Discharge Signals in Oil Ahmad Hafiz Mohd Hashim; Norhafiz Azis; Jasronita Jasni; Mohd Amran Mohd Radzi; Masahiro Kozako; Mohamad Kamarol Mohd Jamil; Zaini Yaakub
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4463

Abstract

Partial discharge (PD) measurements either through electrical or acoustic emission approaches can be subjected to noises that arise from different sources. In this study, the examination on the denoising methods for electrical and acoustic emission PD signal is carried out. The PD was produced through needle-plane electrodes configuration. Once the voltage reached to 30 kV, the electrical and acoustic emission PD signals were recorded and additive white Gaussian noise (AWGN) was introduced. These signals were then denoised using moving average (MA), finite impulse response (FIR) low/high-pass filters, and discrete wavelet transform (DWT) methods. The denoising methods were evaluated through ratio to noise level (RNL), normalized root mean square error (NRMSE) and normalized correlation coefficient (NCC). In addition, the computation times for all denoising methods were also recorded. Based on RNL, NRMSE and NCC indexes, the performances of the denoising methods were analyzed through normalization based on the coefficient of variation (𝐶𝑣). Based on the current study, it is found that DWT performs well to denoise the electrical PD signal based on the RNL and NRMSE 𝐶𝑣 index while MA has a good denoising NCC and computation time 𝐶𝑣 index for acoustic emission PD signal.
Implementing Pseudo-Random Control in Boost Converter: An Effective Approach for Mitigating Conducted Electromagnetic Emissions Zakaria M'barki; Youssef Mejdoub; Kaoutar Senhaji Rhazi; Khalid Sabhi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4832

Abstract

Currently, pulse width modulation (PWM) is a prevalent technique in the field of DC-DC converter control. Its primary objectives encompass maintaining the regulation of the converter's output voltage and improving the load's performance by mitigating the adverse effects caused by harmonic distortions. Unfortunately, the utilization of PWM is associated with significant levels of residual harmonics, characterized by notable amplitudes and frequencies, which have the potential to induce mechanical vibrations, acoustic disturbances, and electromagnetic interference (EMI).To address this challenge, a method known as pseudo-random modulation (PRM) has been developed. In comparison to traditional PWM, PRM offers ease of implementation and high efficacy in EMI mitigation. PRM achieves this by distributing harmonic power across a broader frequency range, thereby reducing the prominence of high-amplitude harmonics at specific frequencies. Within the context of Spread Spectrum Modulation (SSM), this study extensively explores diverse converter topologies and proposes an innovative hardware implementation using the cost-effective Atmega328p microcontroller. Furthermore, the study scrutinizes the consequences of implementing this randomized control strategy to reduce electromagnetic emissions from a Boost converter, a well-recognized source of significant interference in its operational environment. Ultimately, the aim is to evaluate the effectiveness of these applied methodologies in achieving the maximum dispersion of the power spectrum, thereby enhancing overall electromagnetic compatibility.
ACRMiner: An Incremental Approach for Finding Dense and Sparse Rectangular Regions from a 2D Interval Dataset Dwipen Laskar; Anjana Kakoti Mahanta
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4786

Abstract

In many applications, transactions are associated with intervals related to time, temperature, humidity or other similar measures.  The term "2D interval data" or "rectangle data" is used when there are two connected intervals with each transaction. Two connected intervals give rise to a rectangle. The rectangles may overlap producing regions with different density values. The density value or support of a region is the number of rectangles that contain it. A region is closed if its density is strictly bigger than any region properly containing it. For rectangle dataset, these regions are rectangular in shape.In this paper an algorithm named ACRMiner has been proposed that takes as input a sequence of rectangles and computes all closed overlapping rectangles and their density values. The algorithm is incremental and thus is suitable for dynamic environment. Depending on an input threshold the regions can be classified as dense and sparse.Here a tree-based data structure named as ACR-Tree is used. The method has been implemented and tested on synthetic and real-life datasets and results have been reported. Few applications of this algorithm have been discussed. The worst-case time complexity the algorithmis O(n5) where n is the number of input rectangles.

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