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  1. 1
    Group formation using genetic algorithm

    Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

    Published 2009
    “…Due to the increasing of complexity in software projects, group work is becoming more important in order to ensure quality software products can be delivered on time.Thus, in universities, group work is seen as a good preparation for students to industry because by working in group, it can reduce the individual workload,improve the ability to manage a project and enhance the problem solving skills. However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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  2. 2
    Development of mobile location based notification for crime cases tracking as an alternative alert for public safety / Noraini Ismail

    Development of mobile location based notification for crime cases tracking as an alternative alert for public safety / Noraini Ismail by Ismail, Noraini

    Published 2014
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  3. 3
    Multi-floor indoor location estimation system based on wireless local area network

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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  4. 4
    CSC126 - Fundamentals of Algorithms and Computer Problem Solving / Faculty of Computer And Mathematical Sciences

    CSC126 - Fundamentals of Algorithms and Computer Problem Solving / Faculty of Computer And Mathematical Sciences by UiTM, Faculty of Computer And Mathematical Sciences

    Published 2023
    “…This course is an introduction to problem solving using a computer programming language. …”
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    Teaching Resource
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  5. 5
    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language

    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language by Jano, Zanariah, Omar, Norliza, Nazir, Faridah

    Published 2019
    “…The students were to arrange the basic words into grammatical sentences based on the scratch program and write a cake recipe using an algorithmic technique, a series of instructions contained in the scratch program. …”
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  6. 6
    Traveler’s recommendation mobile based system around Terengganu / Muhammad Aiman Syakir Shamsudin

    Traveler’s recommendation mobile based system around Terengganu / Muhammad Aiman Syakir Shamsudin by Shamsudin, Muhammad Aiman Syakir

    Published 2021
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  7. 7
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Faridah Nazir, Zanariah Jano, Norliza Omar

    Published 2019
    “…The students were to arrange the basic words into grammatical sentences based on the scratch program and write a cake recipe using an algorithmic technique, a series of instructions contained in the scratch program. …”
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  8. 8
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Nazir, Faridah, Jano, Zanariah, Omar, Norliza

    Published 2019
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  9. 9
    Comparison Between Linear Programming And Integer Linear Programming: A Review

    Comparison Between Linear Programming And Integer Linear Programming: A Review by Sam, Mei Lee, Saptari, Adi, Salleh, Mohd Rizal, Mohamad, Effendi

    Published 2018
    “…Three criteria were used to evaluate the characteristics: time complexity, problem size and computational time. …”
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  10. 10
    Development of dynamic programming algorithm for maintenance scheduling problem

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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  11. 11
    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…Optimization algorithms can be used to solve Non-deterministic Polynomial (NP) hard problem like system management. …”
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  12. 12
    Using genetic algorithm for solving N-Queens problem

    Using genetic algorithm for solving N-Queens problem by Turky A.M., Ahmad M.S.

    Published 2023
    Conference paper
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  13. 13
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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  14. 14
    Building an Algorithm for Measuring C Programming Assignments Quality

    Building an Algorithm for Measuring C Programming Assignments Quality by Muhd Zulhafriz Aadel bin Marzuki, Muhd Zulhafriz

    Published 2008
    “…The tested programming language is C considering the problems in grading programming assignments are directly related with this subject in UTP.…”
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    Final Year Project
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  15. 15
    Overview of metaheuristic: classification of population and trajectory

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…Algorithms are used to find the solutions through the computer program. …”
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    Monograph
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  16. 16
    Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq

    Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

    Published 2021
    “…This study aims to investigate teaching issues in solving programming problems and find the right approach to teach programming using a suitable problem solving approach method. …”
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  17. 17
    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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  18. 18
    Agent-based extraction algorithm for computational problem solving

    Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

    Published 2015
    “…Modeling Computational Problem Solving (CPS) is the main issue in teaching programming where the given text is needed to be transformed into a model then later into a programming language. …”
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  19. 19
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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  20. 20
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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