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  1. 1
    Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming

    Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

    Published 2012
    “…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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  2. 2
    Implementation of autonomous vehicle navigation algorithms using event-driven programming

    Implementation of autonomous vehicle navigation algorithms using event-driven programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

    Published 2012
    “…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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  3. 3
    Implementation of Color Filtering on FPGA

    Implementation of Color Filtering on FPGA by Mohd Shukor, Mohd Nasir, Lo, H. H., Sebastian, Patrick

    Published 2007
    “…The functionality of the algorithm is first verified in Matlab, simulating the expected output of the system before implementing it onto the FPGA development board. …”
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  4. 4
    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
    “…As for WXES3l82, the thesis cover the development of programming code, the code implementation and testing and the evaluation including discussion about the problem/constraints meed in the coding program development. …”
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    Thesis
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  5. 5
    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
    “…Then, the data of the maintenance team from one of the utilities provider company in Malaysia was collected to be implemented in the development of a dynamic programming algorithm. …”
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    Thesis
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  6. 6
    Development of DNA fragment assembly using idury-waterman algorithm / Nurul Azyanny Mustaffa

    Development of DNA fragment assembly using idury-waterman algorithm / Nurul Azyanny Mustaffa by Mustaffa, Nurul Azyanny

    Published 2013
    “…It is to shows whether the program implemented satisfied the Idury-Waterman algorithm or not. …”
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  7. 7
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Agustina Pertiwi, Dwika Ananda, Subhan, Subhan, Jumanto, Jumanto, Dasril, Yosza, swanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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  8. 8
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Agustina Pertiwi b, Dwika Ananda, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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    Article
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  9. 9
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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  10. 10
    Development of a cost efficient vision system for defects detection / Muhammad Zarif Kamarudin

    Development of a cost efficient vision system for defects detection / Muhammad Zarif Kamarudin by Kamarudin, Muhammad Zarif

    Published 2010
    “…In this project, MATLAB platform is used to program the entire algorithm furthermore implementing Graphical User Interface to communicate between the vision system and the user. …”
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    Monograph
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  11. 11
    Interactive jigsaw puzzle using backtracking algorithm / Amizah Mohd Kamaruzaman

    Interactive jigsaw puzzle using backtracking algorithm / Amizah Mohd Kamaruzaman by Mohd Kamaruzaman, Amizah

    Published 2012
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    Thesis
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  12. 12
    Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad

    Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad by Muhamad, Kamarul Arifin

    Published 2002
    “…Second experiment uses dynamic programmings apply with Wagner and Fischer algorithm.…”
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    Thesis
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  13. 13
    Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition

    Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition by Reyfill Konnik, Charlie Ivan

    Published 2014
    “…This algorithm is designed using an iterative design model, whereby the program is continually tested and improved. …”
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    Final Year Project
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  14. 14
    Implementation of color filtering on FPGA

    Implementation of color filtering on FPGA by P., Sebastian, M.N.B.M., Shukor, H.H., Lo

    Published 2007
    “…The functionality of the algorithm is first verified in Matlab, simulating the expected output of the system before implementing it onto the FPGA development board. …”
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  15. 15
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Much Aziz Muslim, Much Aziz Muslim, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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    Article
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  16. 16
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi b, Dwika Ananda Agustina Pertiwi b, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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  17. 17
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Dwika Ananda Agustina Pertiwi b, Dwika Ananda Agustina Pertiwi b, Subhan b, Subhan b, Jumanto, Jumanto, Nikmah, Tiara Lailatul, Agustina Pertiwi, Dwika Ananda, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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    Article
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  18. 18
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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    Article
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  19. 19
    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning

    New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

    Published 2023
    “…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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  20. 20
    Development of cost efficient vision system for defects detection / Muhammad Zarif Kamarudin

    Development of cost efficient vision system for defects detection / Muhammad Zarif Kamarudin by Kamarudin, Muhammad Zarif

    Published 2010
    “…In this project, MATLAB platform is used to program the entire algorithm furthermore implementing Graphical User Interface to communicate between the vision system and the user. …”
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    Thesis
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