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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 64 Documents
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Search results for , issue "Vol 30, No 1: April 2023" : 64 Documents clear
Feature selection optimization based on genetic algorithm for support vector classification varieties of raisin Yudi Ramdhani; Dhia Fauziah Apra; Doni Purnama Alamsyah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp192-199

Abstract

Grapes are one of the fruit plants that grow that propagate in certain fields. Grapes can be processed into juice, wine, raisins, and so on. Raisins are dried grapes. Raisins have a distinctive taste and aroma. Raisins are a concentrated and nutritious source of carbohydrates, containing antioxidants, potassium, fiber and iron. To increase the accuracy value, the optimize selection genetic algorithm (GA) is used. This research was conducted modeling using the support vector machine (SVM) and SVM algorithms based on optimize selection GA by using the raisin (raisin varieties) dataset obtained from the UCI machine learning repository. The research dataset is divided into training data and testing data. The data sharing will be carried out using the cross validation and split validation operators. Data validation with 10-Fold-validation on the SVM algorithm has the best level of performance among 5 other algorithms such as; Naïve Bayes, K-nearest neighbor (K-NN), decision tree (DT), neural network, and random forest (RF). The SVM algorithm produces accuracy and area under the curve (AUC) values of 87.11% for accuracy and 0.928 for AUC. Optimization in this study using optimize selection GA. SVM based on optimize selection GA produces accuracy and AUC values of 87.67% for accuracy and 0.930 for AUC.
Federated learning for scam classification in small Indonesian language dataset: an initial study Michael Chen; Dareen Kusuma Halim
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp325-331

Abstract

Most digital phishing or scam trick users into fraudulent links and is more effective against users with low technology literacy, like in Indonesia. Machine learning is widely used for scam classification, but most require sending the messages to a centralized server. This induces privacy concern as messages might contain private data. Federated learning (FL) was proposed to allow user devices to train models locally without sending data to server. In this work, we examined the use of FL with gated recurrent unit (GRU) model for classifying scam messages in Indonesian language with small dataset. We provided two FL-based baseline models (FedAvg and daisy-chained algorithms) and a dataset for scam classification in Indonesian language. We examined the models based on these performance metrics; precision, recall, F1, selectivity, and balanced accuracy. Despite the performance, we pointed out characteristics of the FL algorithms and the hyperparameters for this use case as pointers towards fine-tuning these baseline models. Overall, the FL model with FedAvg algorithm performed better in all metrics except recall.
An automatic alignment of the business process and business value models: a novel MDA method Nassim Kharmoum; Sara Retal; Karim El Bouchti; Wajih Rhalem; Soumia Ziti
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp501-509

Abstract

With the massive development of end-users requirements, the model alignment has become an essential stage in software engineering, especially in the model driven architecture (MDA) approach, to absorb the end-user’s need. The purpose is to facilitate the alignment of new models from existing ones. Our contribution in this paper is to deal with the MDA higher abstraction lever by focusing on the automatic alignment of the business value with the business process models for the information system (IS). For our case, the data-flow diagram (DFD) illustrates the business process model, and the E3value model illustrates the business value model. However, the ATLAS-transformation language (ATL) ensures automatic alignment. The main goal is to facilitate and accelerate IS implementation while enhancing its quality.
A study on high dimensional big data using predictive data analytics model Nivethitha Krishnadoss; Lokesh Kumar Ramasamy
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp174-182

Abstract

A massive bulk of data is being created due to digitalisation in various industries, including medical, manufacturing, sales, internet of things (IoT) devices, the web, and businesses. To find data patterns for data attributes machine learning (ML) algorithms are used. In this fast-growing world, we can see that data is generated in abundance by people, machines, and corporations. With the increase in computer science market, researchers are integrating heterogeneous and diverse data into accurate patterns by applying machine learning algorithms and complex strategies on data sets. The overabundance of high-dimensional big data has made it more difficult for scientists to extract important information from these data efficiently. Conventional data mining approaches are ineffective when dealing with large amounts of data. As big data increase exponentially, predictive analytics has become widely known. To evaluate a large number of data patterns, data driven technology predictive big data analytics (PBA) can be used and ML algorithms to investigate the present and future data based on the records of data patterns. In this research paper, predictive analysis on big data has been proposed using the splitting random forest (SRF) methodology with help of hyperparameter optimization and dimension reduction technique.
Integrated approaches in a morphological analyzer of the Arabic language Said Iazzi; Abderrazak Iazzi; Hicham Gueddah; Abdellah Yousfi; Mostafa Bellafkih
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp299-306

Abstract

This article presents a systemof a morphological analyzer of the Arabic language, by integrating several approaches and the viterbi algorithm. First approach is based on database for all thesurface patterns in the Arabic language, second approach is Buckwalter Arabic morphological analyzer and the last approach is based on finite state automaton. With the integration of correspondence tables between affixes in these approaches. The combination between these approaches in our analyzer is very important. Our analyzer is tested on a morphological corpus of 200,000 words, which generalize the words of the Arabic language. The effectiveness of the proposed approaches is demonstrated experimentally and the results obtained are comparable to the state of the art. Moreover, it shows the interest and the advantages of integrating these approaches are to improve our morphological analyzer.
Effect of harmonics on reduction of unbalance in three-phase four wire composite network Ravichandran Durgayandi; Muruganantham Narayanan
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp24-32

Abstract

The unbalanced current drawn by the composite loads in small-scale industries is mainly due to single-phase loads. Any operation of single-phase loads will cause unbalance of current and produce distortion due to non-linear loads. The neutral current is increased and voltage at the load end is reduced due to an increase in unbalanced linear loads. Industries find it difficult to balance the load and control the neutral current. To overcome the problem, this work aims to add a passive network in different configurations along with shunt active power filter. A set of linear and non-linear loads are considered in the network and the results are discussed in this paper. The L and C values are designed to compensate for the required reactive power and the canceling of negative and zero sequence current quantities due to unbalance in the circuit. This paper also reviewed the effect of active filter RMS current at an unbalanced load current.
Personal identification using lip print furrows Tamara Afif Anai; Samira S. Mersal; Mostafa-Sami M. Mostafa
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp460-468

Abstract

There are common techniques for personal identification such as fingerprint recognition, face recognition, and iris recognition. In this paper, we suggest a new method for personal identification using lip print furrows. This method will be useful in forensics services. This study aims to identify people by their lip print patterns that are unique for each person. Lip print features are extracted from the lip print images by using the vertical Sobel operator, diagonal ±45 lines, and hough transform. A lip print pattern was formed for each person containing only the furrows (the extracted features) that were extracted from 3 lip print images for that person. The correlation coefficients and the mean squared error (MSE) are provided and passed to the support vector machine (SVM) for the classification process. The suggested method gives good results. A comparison between the results of the proposed method and other methods was presented.
Features of growth of agricultural crops and factors negatively affecting their growth Moldir Yessenova; Gulzira Abdikerimova; Zhanna B. Sadirmekova; Natalya Glazyrina; Saltanat Adikanova; Adilbek Tanirbergenov; Mukhamedrakhimov Karipola; Galiya Mukhamedrakhimova
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp625-632

Abstract

This article is about methods of analyzing aerial images. Images from Planet.com for crops in North Kazakhstan owned by the Center for Cereal Production and Research. A.I. Barayev. The main goal of the research work is to develop and implement algorithms that allow identifying and distinguishing factors in aerial photographs that adversely affect the growth of plants during the growing season. Spectral brightness coefficient (SBC), normalized difference vegetation index (NDVI), textural features, clustering, and integral transformations are used to solve the problem. Particular attention has been paid to the development of software tools for selecting features that describe textural differences to divide texture regions into subregions. That is weeds, and pests in aerial images. The application of a set of textural features and orthogonal transformations to the analysis of experimental data is explored to identify regions of potentially correlated features in the future. The analysis of the received data made it possible to determine the characteristics of changes in the reflective capacity of agricultural plants and weeds in certain stages of the growing season. The obtained information is of great importance for confirming the observations from space remote from the aerial images.
Comparative study and simulation of advanced MPPT control algorithms for a photovoltaic system Ismail Isknan; Abdellah Asbayou; Abdel Hamid Adaliou; Ahmed Ihlal; Lahoussine Bouhouch
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp46-56

Abstract

A photovoltaic (PV) system uses solar radiation and converts it into electrical energy. An energy management system consisting of a maximum power point tracking (MPPT) charge controller is then necessary. In the present work, for the optimization of the electrical energy delivered by the solar PV panel we will compare four types of controls explained below, namely "MPPT-P&OM", "MPPT-IncM", "MPPT-PI-P&OC" and "MPPT-FOPI-P&OC". Based on these comparisons, for different values of solar irradiance, the four methods seem to perform quite similarly; all four are fast and show small oscillations around the optimal value; nevertheless, the MPPT-IncM method performs slightly better than the others. This is due to the fact that it is slightly faster and has fewer oscillations. The simulation is implemented numerically using the MATLAB/Simulink development tool.
Virtual machine tree task scheduling for load balancing in cloud computing Santosh Kummar Maurya; Suraj Malik; Neeraj Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp388-393

Abstract

The increasing number of publications towards cloud computing proves that much research and development has been done, especially for task scheduling. Organizations are eager to get more customized technology to run the most smoothly in the provision of visual cloud services for fruity users. As the circumstances of Covid indicate to technology that everyone should run digitally, the workload on machines increased. For workload solutions, organizations are trying to balance the situation with the successful operation of cloud services to use appropriate services/resources. Nevertheless, the issues are still to be resolved by researchers, so we respect all my friends who are putting a lot of effort into developing new techniques. A proposed paper is showing a new collation with the load balancing factor by implementing quality of service (QoS) and virtual machine tree (VMT). A CloudSim toolkit will then be used to compare them. A tree structure graph is included in the VMT algorithm to schedule tasks with the appropriate distribution on each machine. The QoS algorithm performs the task of scheduling based on the service required by the user with the best quality and satisfies the user.

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