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  1. 1

    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

    Published 2019
    “…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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    Thesis
  2. 2

    Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner by Salleh Muner, Nur Nabilah

    Published 2019
    “…It provides platform for developing early childhood education that combines learning with play. …”
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    Research Reports
  3. 3

    My little learner: E-learning wonderland by Teoh, Wei En

    Published 2025
    “…The app will also use adaptive learning algorithms to tailor the instructional material to each child's unique learning style and speed. …”
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    Final Year Project / Dissertation / Thesis
  4. 4

    My little learner : E-learning wonderland by Teoh, Wei En

    Published 2025
    “…The app will also use adaptive learning algorithms to tailor the instructional material to each child's unique learning style and speed. …”
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    Final Year Project / Dissertation / Thesis
  5. 5
  6. 6

    Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi by Mohd Azmi, Amalin Aliesya

    Published 2023
    “…The major limitation is the algorithm running speed which can be a little slow when it comes to making recommendations. …”
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    Thesis
  7. 7

    Stress mental health symptom assessment mobile application for young adults by Lee, Chun Hoong

    Published 2023
    “…Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
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    Final Year Project / Dissertation / Thesis
  8. 8

    Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML) by Kabbashi, Nassereldeen Ahmed, Hasan, Tahsin Fuad, Alam, Md Zahangir, Saleh, Tanveer, Hassan Abdalla Hashim, Aisha

    Published 2024
    “…Nine proven classification algorithms were applied to the datasets, successfully classifying the water quality conditions with up to 98% accuracy. …”
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    Article