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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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Integration of an optimized neural network in a photovoltaic system to improve maximum power point tracking efficiency Ezzitouni Jarmouni; Ahmed Mouhsen; Mohamed Lamhamedi; Hicham Ouldzira; Ilias En-naoui
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.pp1276-1285

Abstract

Due to the variability of weather conditions and equipment properties the maximum power point tracking (MPPT) performance is influenced. MPPT controllers are widely used to improve photovoltaic (PV) efficiency because MPPT can produce maximum power under various weather conditions. Among the most used techniques and representing a satisfactory efficiency are those based on artificial intelligence. Since the use of neural networks requires resources at the implementation level, the optimization of these systems is an important phase. This work represents an optimized system for tracking the maximum power point, the latter based on a multi-layer neural network. The optimized multi layer perceptron (MLP) will ensure a fast convergence to the maximum power point with a low oscillation compared to the classical method.
Prediction of patient survival from heart failure using a cox-based model Tsehay Admassu Assegie; Thulasi Karpagam; Sathya Subramanian; Senthil Murugan Janakiraman; Jayanthi Arumugam; Dawed Omer Ahmed
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.pp1550-1556

Abstract

The existing heart failure risk prediction models are developed based on machine learning predictors. The objective of this study is to identify the key risk factors that affect the survival time of heart patients and to develop a heart failure survival prediction model using the identified risk factors. A cox proportional hazard regression method is applied to generate the proposed heart failure survival model. We used the dataset from the University of California Irvine (UCI) clinical heart failure data repository. To develop the model we have used multiple risk factors such as age, anemia, creatinine phosphokinase, diabetes history, ejection fraction, presence of high blood pressure, platelet count, serum creatinine, sex, and smoking history. Among the risk factors, high blood pressure is identified as one of the novel risk factors for heart failure. We have validated the performance of the model via statistical and empirical validation. The experimental result shows that the proposed model achieved good discrimination and calibration ability with a C-index (receiver operating characteristic (ROC) of being 0.74 and a log-likelihood ratio of 81.95 using 11 degrees of freedom on the validation dataset.
Sentiment analysis through twitter as a mechanism for assessing university satisfaction Omar Chamorro-Atalaya; Dora Arce-Santillan; Guillermo Morales-Romero; César León-Velarde; Primitiva Ramos-Salaza; Elizabeth Auqui-Ramos; Miguel Levano-Stella
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.pp430-440

Abstract

Currently, the data generated in the university environment related to the perception of satisfaction is generated through surveys with categorical response questions defined on a Likert scale, with factors already defined to be evaluated, applied once per academic semester, which generates very biased information. This leads us to wonder why this survey is applied only once and why it only asks about some factors. The objective of the article is to demonstrate the feasibility of a proposal to determine the degree of perception of student satisfaction through the use of data science and natural language processing (NLP), supported by the social network twitter, as an element of data collection. As a result of the application of this proposal based on data science, it was possible to determine the level of student satisfaction, being 57.27%, through sentiment analysis using the Python library "NLTK"; Thus, it was also possible to extract texts linked to the relevant factors of teaching performance to achieve student satisfaction, through the term frequency and inverse document frequency (TF-IDF) approach, these being those linked to the use of tools of simulation in the virtual learning process.
Design of current controlled instrumental amplifier by using complementary metallic oxide semiconductor technology Ghanim Thiab Hasan; Kamil Jadu Ali; Ali Hlal Mutlaq
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.pp652-657

Abstract

In this paper, a complementary metal oxide semiconductor (CMOS) instrumental amplifier was designed and implemented in order to provide the possibility of controlling the current and voltage gain. The proposed instrumentation amplifier consists of three conveyors with active resistor. The parasitic resistance value (Rx) was reduced with a large bandwidth level in addition to achieving a high common mode rejection ratio (CMRR). Simulation was performed by using 0.35μm CMOS technology by using the advanced design system (ADS) software. The results obtained prove that the proposed circuit has a good efficiency with higher degree of CMRR in comparison with other amplifiers designed and implemented in other similar works.
Comparison of the efficiency of machine learning algorithms for phishing detection from uniform resource locator Ahana Nandi Tultul; Romana Afroz; Md Alomgir Hossain
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.pp1640-1648

Abstract

We are using cyberspace for completing our daily life activities because of the growth of Internet. Attackers use some approachs, such as phishing, with the use of false websites to collect personal information of users. Although, software companies launch products to prevent phishing attacks, identifying a webpage as legitimate or phishing, is a very defficult and these products cannot protect from attacks. In this paper, an anti-phishing system has been introduced that can extract feature from website’s URL as instant basis and use four classification algorithms named as K-Nearest neighbor, decision tree, support vector machine, random forest on these features. According to the comparison of the experimental results from these algorithms, random forest algorithm with the selected features gives the highest performance with the 95.67% accuracy rate. Then we have used one deep learning algorithm as enhanced of our experiment named as deep neural decision forests which have given performance with the 92.67% accuracy rate. Then we have created a system which can extract the features from raw URL and pass the features to our deep neural decision forest trained model and can classify the URL as Phishing or legitimate.
Performance evaluation of chi-square and relief-F feature selection for facial expression recognition Mayyadah Ramiz Mahmood; Maiwan Bahjat Abdulrazzaq
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.pp1470-1478

Abstract

Pattern recognition is a crucial part of machine learning that has recently piqued scientists' interest. The feature selection method utilized has an impact on the dataset's correctness and learning and training duration. Learning speed, comprehension and execution ease, and properly chosen features influence all high-quality outcomes. The two feature selection methods, relief-F and chi-square, are compared in this research. Each technique assesses and ranks attributes based on distinct criteria. Six of the most important features with the highest ranking have been chosen. The six features are utilized to compare the performance accuracy ratios of the four classifiers: k-nearest neighbor (KNN), naive Bayes (NB), multilayer perceptron (MLP), and random forests (RF) in terms of expression recognition. The final goal of the proposed strategy is to employ the least number of features from both feature selection methods to distinguish the four classifiers' accuracy performance. The proposed approach was trained and tested using the CK+ facial expression recognition dataset. According to the findings of the experiment, RF is the best accurate classifier on chi-square feature selection, with an accuracy of 94.23 %. According to a dataset utilized in this study, the relief-F feature selection approach had the best classifier, KNN, with an accuracy of 94.93 %
Routing flying Ad Hoc network using salp swarm algorithm Alaa Ibrahim Mahmood; Omar Ibrahim Alsaif; Ibrahim Ahmed Saleh
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.pp946-953

Abstract

An Ad-hoc network is collection of mobile nodes without the necessity of existing any centralized access points. In this paper introduce novel protocol that used to improveAdHoc protocol with salp swarm algorithm to routed flying Ad Hoc Network (FANET) by method of simulation. FANET predicated unmanned aerial vehicles (UAV), it designed wireless network has nodes withwith high mobility, actively changing topology and movement in 3D space. The main problem for FANET manner of routing packets among managed nodes. The new protocol based on salp swarm algorithm called “SalpAdHoc” protocol to solve routing problem and less the conjunction, thesimulation results of an experimental study confirming the feasibility of using salp swarm algorithms for routing in FANET are presented.
Investigation into the suitability of kinect sensor for automated body measurement Ejidokun Temitayo; Adigun Samson Olasunkanmi; Olutayo-Irheren E. Olutayo; Rabbilfattah Ozovehe Yusuf
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.pp694-702

Abstract

Due to the low cost and wide availability of the Kinect sensor, researchers and experts in the field of anthropometry, sizing and clothing fiting are leveraging on its inbuilt 3D camera to develop systems for automated body measurement. This study focuses on the evaluation of the Microsoft Kinect (V1) sensor to determine its suitability for automated body measurement. The study was conducted by data collection of various body dimensions of test subjects using a measuring tape as a reference. Furthermore, a statistical approach known as the measurement system analysis was used to investigate the sensor's capability to produce accurate, reliable and consistent body measurements. The results obtained shows indicates that there exists very little variation when the measurement is repeated. Also, the instrument is relatively stable, with minimal bias which can be corrected by calibration. The outcome of the study proves the effectiveness of the Microsoft Kinect sensor as a means of conducting body measurement.
Islamic events reminder system via short message service notifications alert Maha Ibrahim Khaleel; Anwar Hamza Bresam
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.pp1649-1658

Abstract

For persons working in the field of modern technology, the lack of awareness about Islamic events remains a significant obstacle. One of the numerous reasons why the event gets forgotten on its designated date. This prompted the creation of an automatic reminder system with mobile technology integration. This paper has the purpose of assisting people in remembering their daily Islamic events, as well as serving as a model for informing people of Islamic occasions via short message service (SMS) notifications. As a result, the main goal is to develop an Islamic model that uses SMS to inform people. To develop a free system based on the concept of recalling the most significant events in Muslim history in order to keep people informed. (Microsoft Visual Studio.net and Microsoft SQL Server Management Studio Express) as our main database. The text message reminder system is made up of two parts: an SMS application for automatic text messaging and a web-based application for customer registration and automatic reminder scheduling. The automated method delivered 100% of the SMS messages to the participants throughout the pilot testing. Finally, the system displayed a notice indicating that the text messages were successfully despatched, and the application was confirmed to be functional.
Secure authentication and privacy-preserving to improve video streaming vehicle ad-hoc network Akeel Kassim Leaby; Mustafa Khalefa; Mushtaq A. Hasson; Ali A. Yassin
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.pp480-487

Abstract

In vehicular ad hoc networks (VANET), the privacy of vehicle data symbolizes a big challenge towards malicious attacks. On the other side, vehicles in VANET can play a staple role in monitoring the environment by sensing the surrounding environment, compute the sensing information, and transfer the results if needed to the authorized party. Most of the modern VANETs systems encrypt the information to prevent hacking it but mostly neglect the decryption that occurred when data need to re-processed. In this paper, we try to cover this weak point by using fully homomorphic encryption (FHE) because of its specifications. The proposed work focus on twofold: first, create secure authentication and permission management system. While the second is to preserve the privacy of vehicle data that transferred among VANET infrastructure. This scheme also deals with metric security features, such as data privacy, data integrity, and key management. In the experimental results, there is good advance in the fields of interest comparing with the related works.

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