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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  3. 3
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  4. 4
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  5. 5
    Evaluation of data mining models for predicting concrete strength

    Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

    Published 2024
    “…The efficiency and accuracy of concrete strength prediction can be improved by using data mining techniques. A dataset provided by the Department of Civil Engineering of UTAR that consists of 343 samples of concrete strength along with its mixture proportions is used in this project. …”
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  6. 6
    Data Classification and Its Application in Credit Card Approval

    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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  7. 7
    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set

    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Data pre-processing on the data set may improve the classification results. The methods used were over-sampling, under-sampling and hybrid sampling, which modified the data set class distribution to achieve a better result. …”
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  8. 8
    Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm

    Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm by Arief, Akbar, Kartiwi, Mira, Jaswir, Irwandi

    Published 2020
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  9. 9
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The K-means algorithm has been around for over a century. While a rather simplistic and dated algorithm, it remains widely used and taught till this day. …”
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  10. 10
    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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  11. 11
    Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining

    Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

    Published 2023
    “…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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  12. 12
    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
    “…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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  13. 13
    Identifying Relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm

    Identifying Relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah

    Published 2013
    “…Interesting relationships were discovered and the results were compared to earlier findings using the same method on a sample datasets of 50 hearing loss patients with 0.1 as the minimum support and 0.7 confidence thresholdsfor the association rule mining. …”
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  14. 14
    Data mining in mobile ECG based biometric identification

    Data mining in mobile ECG based biometric identification by Sidek, Khairul Azami, Mai, Vu, Khalil, Ibrahim

    Published 2014
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  15. 15
    A hybrid model using genetic algorithm and neural network for predicting dengue outbreak

    A hybrid model using genetic algorithm and neural network for predicting dengue outbreak by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaakob, Razali

    Published 2012
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  16. 16
    Random sampling method of large-scale graph data classification

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Finally, we classified the graphs of data blocks using the SVM algorithm. In experimental evaluation, our proposed method outperformed state-of-the-art graph kernels on graph classification datasets in terms of accuracy.…”
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  17. 17
    The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop

    The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop by Kerdprasop, Nittaya, Kerdprasop, Kittisak

    Published 2014
    “…These representatives are subsequently used in the main process of frequent pattern mining. …”
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  18. 18
    Distribution and health risk assessment of trace metals in freshwater tilapia from three different aquaculture sites in Jelebu Region (Malaysia)

    Distribution and health risk assessment of trace metals in freshwater tilapia from three different aquaculture sites in Jelebu Region (Malaysia) by Low, K.H., Zain, S.M., Abas, R., Salleh, K.M., Teo, Y.Y.

    Published 2015
    “…Results were compared with established legal limits and the daily ingestion exposures simulated using the Monte Carlo algorithm for potential health risks. …”
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  19. 19
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…To test the effectiveness of the proposed algorithm, the real and generated samples is added to training phase to build a prediction model using M5 Model Tree. …”
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  20. 20
    Face recognition using eigenfaces and smooth support vector machine

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…These significant features vector are further refine using Gaussian kernel. An experiment using standard data set from AT&T Laboratories Cambridge with 400 samples of human faces is conducted. …”
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