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  1. 1

    Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

    Published 2018
    “…This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. …”
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    Thesis
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    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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    Conference or Workshop Item
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    Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results by Ahmad Amin, Afifah Munirah, Abdullah, Adilah Syahirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

    Published 2022
    “…Objective: This study aims to predict the academic performance of dental students based on their admission results using Artificial Intelligence. …”
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    Proceeding Paper
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    Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

    Published 2024
    “…And the third objective is to evaluate reverse migration prediction model based on machine learning analysis. For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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    Thesis
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    Optimizing tree planting areas through integer programming and improved genetic algorithm by Md Badarudin, Ismadi

    Published 2012
    “…In conclusion, the hybrid algorithm based solution strategies improved efficiency with convincing results, therefore, this will assist planners for better decision making to optimize area to achieve more trees to be planted. …”
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    Thesis
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    Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

    Published 2025
    “…This study proposes an Intelligent Teacher Placement Selection (ITPS) system based on a Staff Placement Model (SPM), expanding the attribute set to 27 by incorporating personal, staffing position, placement type, and human factors to enhance decision-making fairness. …”
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    Article
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    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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    Conference or Workshop Item
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    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…Grey relational analysis-artificial neural network (GRANN) prediction model was developed based on six slope factors: unit weight, friction angle, cohesion, pore pressure ratio, slope height, and slope angle, with the factor of safety (FOS) as the output factor. …”
    Conference Paper
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    An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

    Published 2012
    “…This thesis presents the model of predicting student academic performances inHigher Learning Institution (HLI).The prediction ofstudentssuccessfulis one of the most vital issues inHLI.In the previous work, thereare many methodsproposed topredictthe performanceof students such as Scholastic Aptitude Test (SAT) or American College Test (ACT), Intelligent Test, Fuzzy Set Theory, Neural Network, Decision Tree and Naïve Bayes.However, thefactremainsfound ina variety of debateamongeducators inhigher learning institution, especially those relatedto predictorvariablesthatused and the resulting level of prediction accuracy.This shown that the rule model in predicting student performanceisstilla gapand it is urgent for educators to obtain a more accurate prediction results.The objective of thisstudyis to create a rule model in predicting of students performance based on their psychometric factors. …”
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    Thesis
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    E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

    Published 2022
    “…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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    Article
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    Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm by Ibrahim, Hamidah, Yasin, Waheed, Abdul Hamid, Nor Asilah Wati, Udzir, Nur Izura

    Published 2014
    “…Moreover, cache pollution is a drawback of traditional web caching policies such as Least Frequently Used (LFU), Least Recently Used (LRU), and Greedy Dual Size (GDS) where web objects that are stored in the cache are not visited frequently. In this work, new intelligent cooperative web caching approaches based on decision tree supervised machine learning algorithm are presented. …”
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    Conference or Workshop Item
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    Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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    Article
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