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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Shahreen Kasim
Universiti Tun Hussein Onn
Computer Science & IT Engineering

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Comparison of meta-heuristic algorithms for fuzzy modelling of COVID-19 illness’ severity classification Nur Azieta Mohamad Aseri; Mohd Arfian Ismail; Abdul Sahli Fakharudin; Ashraf Osman Ibrahim; Shahreen Kasim; Noor Hidayah Zakaria; Tole Sutikno
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i1.pp50-64

Abstract

The world health organization (WHO) proclaimed the COVID-19, commonly known as the coronavirus disease 2019, was a pandemic in March 2020. When people are in close proximity to one another, the virus spreads mostly through the air. It causes some symptoms in the affected person. COVID-19 symptoms are quite variable, ranging from none to severe sickness. As a result, the fuzzy method is seen favourably as a tool for determining the severity of a person’s COVID-19 sickness. However, when applied to a large situation, manually generating a fuzzy parameter is challenging. This could be because of the identification of a large number of fuzzy parameters. A mechanism, such as an automatic procedure, is consequently required to identify the right fuzzy parameters. The metaheuristic algorithm is regarded as a viable strategy. Five meta-heuristic algorithms were analyzed and utilized in this article to classify the severity of COVID-19 sickness data. The performance of the five meta-heuristic algorithms was evaluated using the COVID-19 symptoms dataset. The COVID-19 symptom dataset was created in accordance with WHO and the Indian ministry of health and family welfare criteria. The findings provide the average classification accuracy for each approach.
A systematic literature review of machine learning methods in predicting court decisions Nur Aqilah Khadijah Rosili; Noor Hidayah Zakaria; Rohayanti Hassan; Shahreen Kasim; Farid Zamani Che Rose; Tole Sutikno
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp1091-1102

Abstract

Envisaging legal cases’ outcomes can assist the judicial decision-making process. Prediction is possible in various cases, such as predicting the outcome of construction litigation, crime-related cases, parental rights, worker types, divorces, and tax law. The machine learning methods can function as support decision tools in the legal system with artificial intelligence’s advancement. This study aimed to impart a systematic literature review (SLR) of studies concerning the prediction of court decisions via machine learning methods. The review determines and analyses the machine learning methods used in predicting court decisions. This review utilised RepOrting Standards for Systematic Evidence Syntheses (ROSES) publication standard. Subsequently, 22 relevant studies that most commonly predicted the judgement results involving binary classification were chosen from significant databases: Scopus and Web of Sciences. According to the SLR’s outcomes, various machine learning methods can be used in predicting court decisions. Additionally, the performance is acceptable since most methods achieved more than 70% accuracy. Nevertheless, improvements can be made on the types of judicial decisions predicted using the existing machine learning methods.
A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection Noor Syahirah Nordin; Mohd Arfian Ismail; Tole Sutikno; Shahreen Kasim; Rohayanti Hassan; Zalmiyah Zakaria; Mohd Saberi Mohamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp1146-1158

Abstract

Phishing attack is a well-known cyber security attack that happens to many people around the world. The increasing and never-ending case of phishing attack has led to more automated approaches in detecting phishing attack. One of the methods is applying fuzzy system. Fuzzy system is a rule-based system that utilize fuzzy sets and fuzzy logic concept to solve problems. However, it is hard to achieve optimal solution when applied to complex problem where the process of identify the fuzzy parameter becomes more complicated. To cater this issue, an optimization method is needed to identify the parameter of fuzzy automatically. The optimization method derives from the metaheuristic algorithm. Therefore, the aim of this study is to make a comparative analysis between the metaheuristic algorithms in fuzzy modelling. The study was conducted to analyse which algorithm performed better when applied in two datasets: website phishing dataset (WPD) and phishing websites dataset (PWD). Then the results were obtained to show the performance of every metaheuristic algorithm in terms of convergence speed and four metrics including accuracy, recall, precision, and f-measure. 
Centroidal-polygon: a new modified Euler to improve speed of resistor-inductor circuit equation Nur Shahirah Zulkifli; Nooraida Samsudin; Suzanna Ridzuan Aw; Wan Farah Hanan Wan Osman; Shahreen Kasim; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1399-1404

Abstract

Two types of first-order circuits are resistor-capacitor (RC) and resistorinductor (RL). This paper focuses on the RL circuit equation. The centroidalpolygon (CP) scheme will be tested using SCILAB 6.0 software. This new scheme (CP scheme) is addressed to improve the speed. For the first order circuit equation, the complexity is focused on the time complexity, which is speed of the time taken to complete the simulation in the electrical part. The CP scheme is compared with the previous studies, polygon (P) and harmonic-polygon (HP). The result shows that the CP scheme is less computational and an alternative to solve the first order circuit equation, and get the result quickly compared with the previous research.
Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm Mohd Arfian Ismail; Vitaliy Mezhuyev; Kohbalan Moorthy; Shahreen Kasim; Ashraf Osman Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp27-35

Abstract

This paper present a hybrid method of Newton method, Differential Evolution Algorithm (DE) and Cooperative Coevolution Algorithm (CCA). The proposed method is used to solve the optimisation problem in optimise the production of biochemical systems. The problems are maximising the biochemical systems production and simultaneously minimising the total amount of chemical reaction concentration involves. Besides that, the size of biochemical systems also contributed to the problem in optimising the biochemical systems production. In the proposed method, the Newton method is used in dealing biochemical system, DE for optimisation process while CCA is used to increase the performance of DE. In order to evaluate the performance of the proposed method, the proposed method is tested on two benchmark biochemical systems. Then, the result that obtained by the proposed method is compare with other works and the finding shows that the proposed method performs well compare to the other works.
Application of the Jaya algorithm to solve the optimal reliability allocation for reduction oxygen supply system of a spacecraft Saad Abbas Abed; Mohammad Aljanabi; Noor Hayder Abdul Ameer; Mohd Arfian Ismail; Shahreen Kasim; Rohayanti Hassan; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1202-1211

Abstract

In this paper the reliability of reduction oxygen supply system (ROSS) of a spacecraft which was calculated as a complex system using minimal cut method. The reliability of each component of system was calculated as well as the reliability importance of the system. The cost of each component of the system was possible approaches of the allocation values of reliability based the minimization of the overall cost in this system. The advantage of this algorithm can be used to allocate the optimization of reliability for simple or complex system. This optimization is achieved using the Jaya algorithm. The proposed technique is based on the notion that a conclusion reached on a particular problem should pass near the best results and avoid the worst outcomes. The original findings of this paper are: i) the system used in this paper is a spacecraft’s reduced oxygen supply system with the logarithmic cost function; and ii) the results obtained were by using the Jaya algorithm to solve specific system reliability optimization problems.
Video steganography using 3D distance calculator based on YCbCr color components Esraa Jaffar Baker; Adil Abbas Majeed; Sundos Abdulameer Alazawi; Shahreen Kasim; Rohayanti Hassan; Noor Hidayah Zakaria; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp831-842

Abstract

Steganography techniques have taken a major role in the development in the field of transferring multimedia contents and communications. Therefore, field of steganography become interested as the need for security increased significantly. Steganography is a technique to hide information within cover media so that this media does not change significantly. Steganography process in a video is to hide the information from the intruder and prevent him access to that hidden information. This paper presents the algorithm of steganography in the video frames. The proposed algorithm selected the best frames to hide the message in video using 3D distance equation to increasing difficulty onto the intruder to detect and guess the location of the message in the video frames. As well as selected the best frames in this algorithm increased the difficulty and give us the best stego-video quality using structural similarity (SSIM). Also, the hash function was used to generate random positions to hide the message in the lines of video frames. The proposed algorithm evaluated with mean squared error (MSE), peak signalto-noise ratio (PSNR) and SSIM measurement. The results were acceptable and shows that is the difficulty of distinguishing the hidden message in stego-video with the human eye.
Co-Authors Abdul Sahli Fakharudin Adil Abbas Majeed Ashraf Osman Ibrahim Ashraf Osman Ibrahim Esraa Jaffar Baker Farid Zamani Che Rose Kohbalan Moorthy Mohammad Aljanabi Mohd Arfian Ismail Mohd Saberi Mohamad Noor Hayder Abdul Ameer Noor Hidayah Zakaria Noor Syahirah Nordin Nooraida Samsudin Nur Aqilah Khadijah Rosili Nur Azieta Mohamad Aseri Nur Shahirah Zulkifli Rohayanti Hassan Saad Abbas Abed Sundos Abdulameer Alazawi Suzanna Ridzuan Aw Tole Sutikno Vitaliy Mezhuyev Wan Farah Hanan Wan Osman Zalmiyah Zakaria