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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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Segmentation of data when analyzing the state of telecommunication systems Ilya Lebedev; Babyr Rzayev
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1466-1472

Abstract

The identification of abnormal situations in information and telecommunication systems is considered, based on analyze statistical information of network traffic packages. The method of identifying an anomalous situation based on segmentation of data sample is proposed. The method is aimed at using classifying algorithms that have the best quality indicators on individual data segments. The proposed method will be useful for monitoring information security systems. The method registers of factors that affect the change in the properties of targeted variables. Impact detection allows you to generate data samples, depending on current and expected situations. On the example of the NSL-KDD dataset, there was a division of many data into subset, taking into account the influence of the factors on the range of values. The processing of factors is shown using the change point detection function in the time series. With its use, a division of data sample by the final number of non-intersecting measurable subsets has been made. The results of Accuracy, Precision, F-Measure, Recall for various classifiers are shown. The proposed method allows to increase the quality indicators of classification in continuously changing operating conditions of telecommunication systems.
An extensible framework for recurrent breast cancer prognosis using deep learning techniques Reddy Shiva Shankar; Ravi Swaroop Chigurupati; Priyadarshini Voosala; Neelima Pilli
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp931-941

Abstract

Due to population growth, early illness detection is getting more challenging. Breast cancer is the second-deadliest malignancy. An estimated one million people are newly diagnosed with the disease annually in India. Most cases are never diagnosed because they are either ignored or not reported. Also, secondary malignancies may develop after a breast cancer recurrence, including those of the brain, lungs, and bones. Early detection and treatment of people with recurring breast cancer may help prevent secondary cancers and other disorders. By examining cell and tumour data as well as data from other diseases, this project hopes to overcome this obstacle and more accurately diagnose breast cancer. Accurate diagnosis of breast cancer may be achieved with the use of machine learning techniques. The effort focuses on recurring breast cancer and aims to efficiently identify it. In ensemble learning, decision trees filter out non-essential qualities. Cancer recurrences and non-recurrences are distinguished using voting classifiers. The soft voting classifier classifies a variety of data sets with 98.24% accuracy. The proposed model has an accuracy of 0.97, a recall of 0.97, an F1-Score of 0.969, and a Choen kappa score of 0.9655, as stated by the recommended model.
A prediction model based machine learning algorithms with feature selection approaches over imbalanced dataset Alaa Khalaf Hamoud; Mohammed Baqr Mohammed Kamel; Alaa Sahl Gaafar; Ali Salah Alasady; Aqeel Majeed Humadi; Wid Akeel Awadh; Jasim Mohammed Dahr
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp1105-1116

Abstract

The educational sector faced many types of research in predicting student performance based on supervised and unsupervised machine learning algorithms. Most students' performance data are imbalanced, where the final classes are not equally represented. Besides the size of the dataset, this problem affects the model's prediction accuracy. In this paper, the Synthetic Minority Oversampling Technique (SMOTE) filter is applied to the dataset to find its effect on the model's accuracy. Four feature selection approaches are applied to find the most correlated attributes that affect the students' performance. The SMOTE filter is examined before and after applying feature selection approaches to measure the model's accuracy with supervised and unsupervised algorithms. Three supervised/unsupervised algorithms are examined based on feature selection approaches to predict the students' performance. The findings show that supervised algorithms (LMT, Simple Logistic, and Random Forest) got high accuracy after applying SMOTE without feature selection. The prediction accuracies of unsupervised algorithms (Canopy, EM, and Farthest First) are enhanced after applying feature selection approaches and SMOTE filter.
Towards an approach based on particle swarm optimization for Arabic named entity recognition on social media Brahim Ait Ben Ali; Soukaina Mihi; Ismail El Bazi; Nabil Laachfoubi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1589-1600

Abstract

Named entity recognition is an essential task for various applications related to natural language processing (NLP). It aims to retrieve a variety of named entities (NEs) from text and categorize them according to predetermined target categories. In many cases, using the entire feature set can be time-consuming and negatively impact the performance. Moreover, it is challenging to find the relevant subsets of features for a particular task due to the high number. The feature selection technique is an unsupervised process for selecting informative features by creating a new subset of informative features. This technique is used to enhance the underlying algorithm's performance. This article implements an effective feature selection algorithm using particle swarm optimization (PSO) to identify and classify the Arabic NEs in the text from social media. PSO is a search algorithm that utilizes a population of particles in a multidimensional space. The proposed method is evaluated using two publicly available Arabic Dialect social media datasets. It is demonstrated through comparisons with both baselines and previous models that the new approach achieves significant accuracy with considerably reduced feature sets in all parameters.
Congestion aware and game based odd even adaptive routing in network on chip many-core architecture Radha Doraisamy; Minal Moharir; Rajakumar Arul
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp962-972

Abstract

The era of single processors had almost reached a saturation state, and the industry had moved to multi-core processors for the newer generation of many-core architecture. Interconnections between multiple cores with network on chip (NoC) surpass traditional bus architecture for its quality of service (QoS) and other additional services. Seamless communication among the cores is more significant for better performance and the proper utilization of the cores. The rise in the cores count in a semiconductor chip adds the complexity of the communication among cores. Cache misses request and packet transmission’s traffic possibly will reduce the performance of the architecture. A theoretical game-based methodology is proposed to improvise the performance and communication by routing the request packets in the NoC of the many core architectures and the throughput is maximized with reduced latency by using the stag-hunt game (SHG) model. The proposed communication algorithm routes the packets in an adaptive way by detecting the congestion in routers. The SHG based odd-even routing algorithm is adaptive and can divert the packets towards less congested routers using the information gathered about congestion in the system, so that the overall performance of the system in terms of latency and throughput is improved.
Simulation model of proportional integral controller-PWM DC-DC power converter for DC motor using MATLAB Salam Waley Shneen; Ahlam Luaibi Shuraiji; Kassim Rasheed Hameed
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp725-734

Abstract

Smoothly speed range changing, easily speed controlling, and swiftly dynamic response for load torque changing are the main merits which are delivered by direct current (DC) motors. They are also distinguished by their versatility. All these characteristics make the DC motors suitable candidates for various applications. An accurate high-speed control with a good dynamic response, would be of demand for many applications of the DC motors. Controlling the speed of motors using conventional systems is one of the most important method that is adopted and it can be more efficient when used with electronic power devices to control the output voltage. Hence, this paper introduces an efficient proportional integral (PI) speed controller for DC motor fed by direct current-direct current (DC-DC) convertor, which is switched by pulse-width modulation technique. MATLAB/Simulink environment is used to build the whole system. Two operation scenarios have been conducted including constant load with variable speed and variable load with constant speed.
Advanced virtual inertia control against wind power intermittency Muhammad Abdillah; Syailendra Andi; Teguh Aryo Nugroho; Herlambang Setiadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1256-1265

Abstract

Rapid industrial development requires more energy to support their manufacturing processes. Unfortunately, conventional energy was mostly utilized as a primary energy source which is unfriendly to nature and can damage the environment. Nowadays, the transformation from the use of conventional energy to renewable energy sources is increasingly being socialized throughout the world. However, the existence of renewable energy poses new challenges in the world of electricity systems where their effect is reducing the inertia (inertialess) value of conventional energy such as thermal generators. This condition causes frequency oscillations and leads to blackout the electricity system. To overcome this problem, this paper proposed advanced virtual inertia control (VIC) based on an superconducting magnetic energy storage (SMES) employed to accommodate the effects of the integration of renewable energy into the electric power system. SMES was choosen because it has a fast response and an efficiency rate of up to 90%. A two-area power system model was utilized to examine the proposed VIC model based on SMES. From the simulation results, VIC based on has succeeded in reducing frequency oscillations by compressing the system overshoot and reducing the settling time to steady-state.
Enhancement of motor speed identification using artificial neural networks Arshad B. Salih; Zuhair Shakor Mahmood; Ardm Haseeb Mohammed Ali; Ali Najdet Nasret
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1388-1396

Abstract

In this study have been utilized a modified version of ant colony optimization to improve the thresholds of neural networks and weights by including therank-weight approach. Furthermore, this technique easily overcome the drawbacks speed up convergence into the minimum while training the backpropagation neural network. The improved ant colony optimization-backpropagation neural.not only has the capacity to map extensively, but it also enhances operating efficiency noticeably, according to the simulation findings. The simulation results revealed that the speed sensor replaced with the ant colony optimization rw-optimized back propagation neural network-speed identification and motor’s speed determined using this approach the result is satisfactory.
Game innovation: a case study using the Kizzugemu visual novel game with Tyranobuilder software in elementary school Hamidulloh Ibda; Nur Rira Febriani; Muhammad Fadloli Al Hakim; Silviana Nur Faizah; Andrian Gandi Wijanarko; Nanang Qosim
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp460-469

Abstract

This research aims to find out the innovation of the Kizzugemu visual novel game with TyranoBuilder software in elementary school Javanese language learning. The lack of game media innovation in elementary school Javanese language learning is the background of this research. The research method is descriptive and qualitative, with data mining techniques; observation, indepth interviews, and documentation that present the results of descriptions of the innovation, features, application, and impact of using the game in elementary Javanese language learning. The research subjects were the class teacher and 24 fifth-grade students of Madrasah Ibtidaiyah Ma’arif Bulurejo Magelang, Indonesia. The results showed the game’s innovation in multimedia-based game updates, applications, videos, sounds, and texts with the meaning of children’s games in Javanese, Javanese alphabet, Indonesian, and English. Game features are in the form of reading text in each scene and visualized in the material of the Javanese language. The implementation of the game is carried out through five stages which impact teacher awareness, learning media innovation, improved learning outcomes, activeness, understanding of Javanese, and support from parents and schools. Future research needs to explore visual novel game innovation through the latest software.
Characterization of tin selenide nanoparticle films generating from plasma arc penetration of a temperature-varying field Hakima A. Abdulla; Nadheer Jassim Mohammed; Aseel Mustafa Abdul Majeed
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp678-686

Abstract

Using the pulsed laser deposition (PLD) method, tin selenide (SnSe) nanoparticles thin films are created on quartz substrates, which are held at different penetration field temperatures Tp-f (Tp-f is the penetration field temperature to which the plasma arc is exposed) (300, 373, 473, and 573) K. X-ray powder diffraction (XRD) reveals a phase transformation from a hexagonal to an orthorhombic structure. The energy gap, which ranges from 1.748-3.15 eV with direct electronic transmission, is calculated using transmittance spectra. Particle size increases by Tp-f increases. Photoluminescence (PL) intensity and film thickness are inversely proportional to each other. Changing the ratio of the compositions provides an essential strategy for altering a material's melting point as well as its energy gap.

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