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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 65 Documents
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Search results for , issue "Vol 28, No 3: December 2022" : 65 Documents clear
Simulation and analysis of the distributed photovoltaic generation systems based on DIgSILENT power factory Majli Nema Hawas; Ihsan Jabbar Hasan; Mohannad Jabbar Mnati
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.pp1227-1238

Abstract

The voltage stability of the system has become an important component for the steady and dependable functioning of the power system as a result of multiple blackouts around the world (particularly in Iraq). Distributed photovoltaic systems are a subset of decentralized power generating systems that generate electricity using renewable energy sources like solar cells, wind turbines, and water power plants. In order to size a solar-grid-connected home system properly and to confirm the impact of photovoltaics on the system, this article will also do a steady-state analysis. The heating and cooling loads were taken into account when evaluating the residential load profile. With the help of predicted energy use, the photovoltaic (PV) system was sized. The solar system's power output was calculated, and the key variables affecting system performance were examined. The DigSilent power factory 15.2 was used to simulate all of the investigations. This article achieves better system stability outcomes.
Vote algorithm based probabilistic model for phishing website detection Md. Sazzadul Islam Islam Prottasha; Md. Zihadur Rahman; ABM Kabir Hossain; Samia Ferdous Mou; Md. Bulbul Ahmed; M. Shamim Kaiser
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.pp1582-1591

Abstract

Internet scams have been a major concern for everyone over the past decade. With the advancement of technology, attackers have formulated different kinds of contemporary fraudulent procedures to obtain user’s sensitive information. Phishing is one of the oldest and common fraudulent attempts by which every year millions of internet users fall victim to scams resulting in losing their money. Different techniques and algorithms have been proposed by researchers in detecting phishing websites. However, the detection of phishing websites has few challenges since there are different subjective considerations and ambiguities involved in the detection process. This paper presents a two-stage probabilistic method for detecting phishing websites based on the vote algorithm. In the first stage, 29 different base classifiers have been used and their probabilistic values were calculated. In the second stage, the voting algorithm aggregated the probabilistic values of several base classifiers and the phishing websites were detected using the average of probabilities approach. The voting technique achieved an accuracy of 97.431% outperforming all of the single base classifiers in terms of accuracy.
Empirical evidence of phishing menace among undergraduate smartphone users in selected universities in Nigeria Maureen Ifeanyi Akazue; Arnold Adimabua Ojugo; Rume Elizabeth Yoro; Bridget Ogheneovo Malasowe; Obinna Nwankwo
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.pp1756-1765

Abstract

In our exploratory quasi-experimental study, 480-student were recruited and exposed to social engineering directives during a university orientation week. The directives phishing attacks were performed for 10 months in 2021. The contents attempted to elicit personal user-data from participants, enticing them to click compromised links. The study aimed to determine cybercrime risks among undergraduates in selected universities in Nigeria, observe responses to socially-engineered attacks, and explore their attitudes to cybercrime risks before/after such attacks. The study generalized that all participants have great deal awareness of cybercrime, and also primed all throughout study to remain vigilant to scams. The study explores various types of scam and its influence on students’ gender and age on perceived safety on susceptibility to phishing scams. Results show that contrary to public beliefs, none of these factors were associated with scam susceptibility and vulnerability rates of the participants.
A secure framework of blockchain technology using CNN long short-term memory hybrid deep learning model Gillala Chandra Sekhar; Aruna Rajendran
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.pp1786-1795

Abstract

Generation Z is embracing blockchain technology, which is appropriate for the digital age. Internet of things (IoT) can benefit from blockchain technology IoT. The proliferation of IoT technology has led to breakthroughs in distributed system architecture. For the blockchain network to store, communicate, and exchange data, it needs a randomized data management system. This shows how difficult it may be to provide consistent and safe data replication in a distributed system, an issue blockchain technology may overcome. We need a solid prediction model that improves results. This article describes an innovative way to overcome the limitations of third-party transactions using Bitcoin. In this article, convolutional neural networks-long short term memory (CNN-LSTM) deep learning forecasting models are introduced. Convolutional layers help extract relevant data from instances. It has an long short-term memory (LSTM) layer, which lets it find long-and short term dependencies. The experiment's goal was to test the multivariate statistical model we suggested and compare its performance to well-established models. The addition of convolutional layers to a forecasting model may improve its accuracy, according to an experiment. The research shows that this strategy has a better chance of success and is more trustworthy than others.
Enhancement of traveling wave semiconductor optical amplifier approach for DWDM communication system Ahmed A. Amer; Ahmed Abdulelah; Alaa A. Mashkor; Adnan Sabbar
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.pp1541-1547

Abstract

In this study, the high performance of dense wavelength division multiplexing (DWDM) by using a traveling wave semiconductor optical amplifier (TW-SOA) at a channel spacing of 100 GHz is investigated, in terms of (Q-factor, injected current, transmitted power, gain). The Optisystem software is employed to send the different range of input power over the different ranges of the TW-SOA injected current with optimized TW-SOA parameters. The data rate of trans- mission optical signal up to 300 Gb/s at -35 dB input signal power have been investigated. The better results have been measured of the information signal with high quality and gain, when the range of input power is corresponding to the optimized range of injected current for the signal to be transmitted effec- tively. The present communication also supports various numbers of users with the same data rate of 5 Gb/s which is used to check the high quality of the signal in the receiver.

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