Mohamad Afendee Mohamed
Universiti Sultan Zainal Abidin

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

University course timetabling model using ant colony optimization algorithm approach Munirah Mazlan; Mokhairi Makhtar; Ahmad Firdaus Khair Ahmad Khairi; Mohamad Afendee Mohamed
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp72-76

Abstract

Due to the increased number of students and regulations, all educational institutions have renewed their interest to appear in the number of complexity and flexibility since the resources and events are becoming more difficult to be scheduled. Timetabling is the type of problems where the events need to be organized into a number of timeslots to prevent the conflicts in using a given set of resources. Thus in the intervening decades, significant progress has been made in the course timetabling problem monitoring with meta-heuristic adjustment. In this study, ant colony optimization (ACO) algorithm approach has been developed for university course timetabling problem. ACO is believed to be a powerful solution approach for various combinatorial optimization problems. This approach is used according to the data set instances that have been collected. Its performance is presented using the appropriate algorithm. The results are arguably within the best results range from the literature. The performance assessment and results are used to determine whether they are reliable in preparing a qualifying course timetabling process.
Colored object detection using 5 dof robot arm based adaptive neuro-fuzzy method Mujiarto Mujiarto; Asari Djohar; Mumu Komaro; Mohamad Afendee Mohamed; Darmawan Setia Rahayu; W. S. Mada Sanjaya; Mustafa Mamat; Aceng Sambas; Subiyanto Subiyanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp293-299

Abstract

In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based on Arduino microcontroller is applied to the dynamic model of 5 DoF Robot Arm presented. MATLAB is used to detect colored objects based on image processing. Adaptive Neuro Fuzzy Inference System (ANFIS) method is a method for controlling robotic arm based on color detection of camera object and inverse kinematic model of trained data. Finally, the ANFIS algorithm is implemented in the robot arm to select objects and pick up red objects with good accuracy.
Spam detection by using machine learning based binary classifier Mohd Fadzil Abdul Kadir; Ahmad Faisal Amri Abidin; Mohamad Afendee Mohamed; Nazirah Abdul Hamid
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp310-317

Abstract

BecauseĀ of its ease of use and speed compared to other communication applications, email is the most commonly used communication application worldwide. However, a major drawback is its inability to detect whether mail content is either spam or ham. There is currently an increasing number of cases of stealing personal information or phishing activities via email. This project will discuss how machine learning can help in spam detection. Machine learning is an artificial intelligence application that provides the ability to automatically learn and improve data without being explicitly programmed. A binary classifier will be used to classify the text into two different categories: spam and ham. This research shows the machine learning algorithm in the Azure-based platform predicts the score more accurately compared to the machine learning algorithm in visual studio, hybrid analysis and JoeSandbox cloud.
An ant colony algorithm for universiti sultan zainal abidin examination timetabling problem Ahmad Firdaus Khair; Mokhairi Makhtar; Munirah Mazlan; Mohamad Afendee Mohamed; Mohd Nordin Abdul Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp191-198

Abstract

The real-life construction of examination timetabling problem is considered as a common problem that always encountered and experienced in educational institution whether in school, college, and university. This problem is usually experienced by the academic management department where they have trouble to handle complexity for assign examination into a suitable timeslot manually. In this paper, an algorithm approach of ant colony optimisation (ACO) is presented to find an effective solution for dealing with Universiti Sultan Zainal Abidin (UniSZA) examination timetabling problems. A combination of heuristic with ACO algorithm contributes the development solution in order to simplify and optimize the pheromone occurrence of matrix updates which include the constraints problem. The implementation of real dataset instances from academic management is applied to the approach for generating the result of examination timetable. The result and performance that obtained will be used for further use to evaluate the quality and observe the solution whether our examination timetabling system is reliable and efficient than the manual management that can deal the constraints problem.
An Efficient Schema of a Special Permutation Inside of Each Pixel of an Image for its Encryption Hana Ali-Pacha; Naima Hadj-Said; Adda Ali-Pacha; Mustafa Mamat; Mohamad Afendee Mohamed
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i2.pp496-503

Abstract

The developments of communications and digital transmissions have pushed the data encryption to grow quickly to protect the information, against any hacking or digital plagiarisms. Many encryption algorithms are available on the Internet, but it's still illegal to use a number of them. Therefore, the search for new the encryption algorithms is still current. In this work, we will provide a preprocessing of the securisation of the data, which will significantly enhance the crypto-systems. Firstly, we divide the pixel into two blocks of 4 bits, a left block that contains the most significant bit and another a right block which contains the least significant bits and to permute them mutually. Then make another permutation for each of group. This pretreatment is very effective, it is fast and is easy to implement and, only consumes little resource.