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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Yun-Huoy Choo
Universiti Teknikal Malaysia Melaka

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I-OnAR: a rule-based machine learning approach for intelligent assessment in an online learning environment Shaiful Bakhtiar bin Rodzman; Nordin Abu Bakar; Yun-Huoy Choo; Syed Ahmad Aljunid; Normaly Kamal Ismail; Nurazzah Abd Rahman; Marshima Mohd Rosli
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp1021-1028

Abstract

Intelligent systems are created to automate decision making process that is similar to human intelligence. Incorporating intelligent component has achieved promising results in many applications, including in education. Intelligence modules in a tutoring system would bring the application and its capability closer to a human's ability to serve its human users and to solve problems. However, the majority of the online learning provided in the literature review especially in Malaysia, normally only provide the lecture notes, assignments and tests and rarely suggest or give feedbacks on what the students should study or do next in order to fully understand the subjects. Hence, the researchers propose an online learning environment called Intelligent Online Assessment and Revision (I-OnAR). It facilitates the learning process at multiple learning phases such as test creation, materials revision, feedback for improvement and performance analysis. These components are incorporated into the tutoring system to assist self-pace learning at anytime and anywhere. The intelligent agent uses a Rule-based Machine Learning method for the adaptive capabilities such as automated test creation and feedbacks for improvement. The system has been tested on a group of students and found to be useful to support learning process. The results have shown that 60% of the subjects’ performance have improved with the help of the system. The students were given feedbacks on the topic they did poorly as well as how to improve their performance. This proves that the Intelligent Online Assessment and revision (I-OnAR) can be a useful tool to help online students intelligently, systematically and efficiently. For the future works, the researchers would like to apply the usage of other techniques such as Fuzzy Logic to strengthen the analysis and decision of the current system.
Dynamic real-time capacity constrained routing algorithm for evacuation planning problem Jawad Abusalama; Sazalinsyah Razali; Yun-Huoy Choo; Lina Momani; Abdelrahman Alkharabsheh
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i3.pp1388-1396

Abstract

Usually, disasters occur over a relatively short time anytime and anywhere. Most occupancies do not have absolute knowledge about the prevention or safety consciousness to deal with disasters. During disaster occurrence, evacuation processes are conducted to save people’s life, and if there is no appropriate evacuation plan, the situation will become worse. Thus, finding an optimal planning technique to evacuate occupants is critical in many cases i.e. emergency evacuation. In this paper, a Dynamic Real-Time Capacity Constrained Routing (DRTCCR) Algorithm has been proposed and analyzed. Such algorithm will investigate the capacity constraints of the evacuation network in real time by modelling the capacities based on time series to improve current solutions of the Emergency Route Planning (ERP) problem.  Such algorithm will produce an optimal solution for the ERP problem. Performance evaluation on many network models illustrates that the DRTCCR algorithm improves the previous evacuation planning by reducing the evacuation time as well as the computational cost. In addition, DRTCCR algorithm has the ability to recalculate and find out the optimal path dynamically in real time irrespective of the number of trapped people as well as the transportation network size. Analytical experiments have been carried out, which illustrates the efficiency of the proposed algorithm.
An enhanced approach for solving winner determination problem in reverse combinatorial auctions Jawad Abusalama; Sazalinsyah Razali; Yun-Huoy Choo
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.pp934-945

Abstract

When a disaster occurs, the single agent does not have complete knowledge about the circumstances of the disaster. Therefore, the rescue agents should coordinate with each other to perform their allocated tasks efficiently. However, the task allocation process among rescue agents is a complex problem, which is NP-complete problem, and determining the rescue agents that will perform the tasks efficiently is the main problem, which is called the winner determination problem (WDP). This paper proposed an enhanced approach to improve rescue agents’ tasks allocation processes for WDP in reverse combinatorial auctions. The main objective of the proposed approach is to determine the winning bids that will perform the corresponding tasks with minimum cost. The task allocation problem in this paper was transformed into a two-dimensional array, and then the proposed approach was applied to it. The main contribution of the proposed approach is to shorten the search space size to determine the winners and allocate the corresponding tasks for a combination of agents (i.e., more than two agents). The proposed approach was compared to the genetic algorithm regarding the execution time, and the results showed good performance and effectiveness of the proposed approach.
Co-Authors Abdelrahman Alkharabsheh Jawad Abusalama Lina Momani Marshima Mohd Rosli Nordin Abu Bakar Normaly Kamal Ismail Nurazzah Abd Rahman Sazalinsyah Razali Shaiful Bakhtiar bin Rodzman Syed Ahmad Aljunid