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  1. 1
    Using algorithmic taxonomy to evaluate lecturer workload

    Using algorithmic taxonomy to evaluate lecturer workload by Hashim, Ruhil Hayati, Abdul Hamid, Jamaliah, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Mohayidin, Mohd Ghazali

    Published 2006
    “…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  2. 2
    Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm

    Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm by Foo, Yao Heng

    Published 2025
    “…University course timetabling problem (UCTP) is a scheduling problem that requires courses to be assigned to the limited time slots, classrooms, and lecturers, while adhering to a set of predefined constraints. …”
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    Final Year Project / Dissertation / Thesis
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  3. 3
    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal

    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  4. 4
    Performance analysis of resource allocation downlink for MIMO-OFDMA system using greedy algorithm / Azrinawati Samaon

    Performance analysis of resource allocation downlink for MIMO-OFDMA system using greedy algorithm / Azrinawati Samaon by Samaon, Azrinawati

    Published 2016
    “…The proposed algorithm shows comparison between the noise to sub-channel ratio and power allocation among of data sub-channel for 25, 75 and 100 users. …”
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  5. 5
    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal

    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hassan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  6. 6
    Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah

    Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

    Published 2024
    “…At the end of this study, it is recommended that future research might reassess the model by considering additional variables or techniques that may help improve the predictive accuracy. The predictive algorithm can also be added to the Learning Management System along with a dashboard so that it is easier to do analyses in the future.…”
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  7. 7
    Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment

    Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment by Babakura, Abba, Sulaiman, Md Nasir, Mustapha, Norwati, Kasmiran, Khairul A.

    Published 2014
    “…The implementation has been carried out in such a way that quality information is acquired among the systems to demonstrate the effectiveness of decision making among events in the smart home environment.…”
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  8. 8
    Evaluate the performance of university timetabling problem with various artificial intelligence techniques

    Evaluate the performance of university timetabling problem with various artificial intelligence techniques by Hooi, Charmaine Wai Yee

    Published 2025
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    Final Year Project / Dissertation / Thesis
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  9. 9
    Automated study plan generator using rule-based and knapsack problem

    Automated study plan generator using rule-based and knapsack problem by Salahuddin, Lizawati, Hashim, Ummi Rabaah, Salahuddin, Lizawati

    Published 2022
    “…A quantitative methodology through expert’s reviews and questionnaire survey was conducted to evaluate the accuracy of the proposed algorithm. The proposed algorithm shows high accuracy. …”
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  10. 10
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…Besides, classification and prediction are among the popular tasks in machine learning especially for information elicitation. …”
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    Research Reports
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  11. 11
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  12. 12
    Content-based recommender system for an academic social network / Vala Ali Rohani

    Content-based recommender system for an academic social network / Vala Ali Rohani by Vala Ali, Rohani

    Published 2014
    “…The situation, however, leads to a great challenge in terms of information overload among social network users. Recommender systems (RSs) alleviate this problem with a technique that suggests relevant information from the abundance of Web data by considering the user’s previous preference. …”
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  13. 13
    Using web questionnaire for web-based course evaluation: advantages and disadvantages

    Using web questionnaire for web-based course evaluation: advantages and disadvantages by Fariborzi, Elham, Abu Bakar, Kamariah, Kasa, Zakaria, Abu Samah, Bahaman, Abdullah, Muhammad Taufik

    Published 2017
    “…This article examines some advantages and disadvantages of conducting Web survey research especially for Web-based course evaluation at Iranian university E-learning centers. …”
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  14. 14
    Revisit of statistical selection algorithm for peer-to-peer system

    Revisit of statistical selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun

    Published 2008
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  15. 15
    Reconstruction Algorithm In Ofdm System

    Reconstruction Algorithm In Ofdm System by Hwong, Sing Pui

    Published 2017
    “…Channel estimation (CE) in OFDM system is compulsory to obtain the channel state information (CSI) at the receiver. …”
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    Monograph
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  16. 16
    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid

    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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  17. 17
    Exam timetable for unimas-enhancement of sistem jadual waktu UNIMAS

    Exam timetable for unimas-enhancement of sistem jadual waktu UNIMAS by Voon, Tze Min

    Published 2005
    “…A proper searching method and algorithm is not applied for that system. Hence, the Unimas Examination Timetabling System is developed. …”
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    Final Year Project Report / IMRAD
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  18. 18
    Quality-driven scheduling for long-term evolution system

    Quality-driven scheduling for long-term evolution system by Mohd. Ramli, Huda Adibah, Sandrasegaran, Kumbesan, Patachaianand, Rachod

    Published 2011
    “…The proposed algorithm utilises Channel Quality Information (CQI), average throughput, type of services, packet delay and buffer information when allocating and assigning the available Radio Resource Units (RRUs) among the users. …”
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  19. 19
    CSC562: Information Retrieval and Searching Algorithms / College of Computing, Informatics and Media

    CSC562: Information Retrieval and Searching Algorithms / College of Computing, Informatics and Media by UiTM, College of Computing, Informatics And Media

    Published 2022
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    Teaching Resource
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  20. 20
    CSC742 - Storage and Retrieval Algorithms / College of Computing, Informatics and Media

    CSC742 - Storage and Retrieval Algorithms / College of Computing, Informatics and Media by UiTM, College of Computing, Informatics and Media

    Published 2022
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