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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  2. 2
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  3. 3
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  4. 4
    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan

    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan by Nik Mazlan, Nik Aidil Syawalni

    Published 2024
    “…The motifs and textures each convey distinct philosophical perspectives on life. The classification of certain patterns may vary due to differences in the perspectives of individual classifiers, leading to potential inconsistencies. …”
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  5. 5
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  6. 6
    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…Recently, the swarm-based hybrid algorithms have given significant performance in cancer classification. …”
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  7. 7
    The Perspective Classification of Balanced Scorecard with Ontology Technique

    The Perspective Classification of Balanced Scorecard with Ontology Technique by Kaewninprasert, Kittisak, Chai-Arayalert, Supaporn, Yamaqupta, Narueban

    Published 2024
    “…This paper aims to present the Perspective Classification of Balanced Scorecard with Ontology (PCBSC-Onto) framework for automatically classifying performance indicators into BSC’s four perspectives using an ontological approach to support the dynamic capability of the management system’s performance. …”
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  8. 8
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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  9. 9
    Naive bayes-guided bat algorithm for feature selection.

    Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

    Published 2013
    “…Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. …”
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  10. 10
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  11. 11
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  12. 12
    An improved directed random walk framework for cancer classification using gene expression data

    An improved directed random walk framework for cancer classification using gene expression data by Seah, Choon Sen

    Published 2020
    “…From the perspective of computing, an algorithm is developed to ease the diagnosis process, but the feasibility is not reliable. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  14. 14
    Naive Bayes-guided bat algorithm for feature selection

    Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

    Published 2023
    “…Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. …”
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  15. 15
    Assessment of cognitive load using multimedia learning and resting states with deep learning perspective

    Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

    Published 2019
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  16. 16
    Talkout : Protecting mental health application with a lightweight message encryption

    Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

    Published 2022
    “…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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  17. 17
    Iban Plaited Mat Motif Classification using Adaptive Smoothing

    Iban Plaited Mat Motif Classification using Adaptive Smoothing by Silvia, Joseph

    Published 2024
    “…To address this issue, an improved classification method with adaptive smoothing is proposed. …”
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  18. 18
    Comparison between fuzzy and non-fuzzy classification methods in the prediction of residential household water leakage / Nor Aishah Md Noh, Dr. Khairul Anwar Rasmani and Nur Rasyida Mohd Rashid

    Comparison between fuzzy and non-fuzzy classification methods in the prediction of residential household water leakage / Nor Aishah Md Noh, Dr. Khairul Anwar Rasmani and Nur Rasyid... by Md Noh, Nor Aishah, Rasmani, Khairul Anwar, Mohd Rashid, Nur Rasyida

    Published 2013
    “…Therefore this research looks into the potential use of fuzzy rule-based approaches from a new perspective where mathematical models generated using data related to water collected from the consumer consumption. …”
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  19. 19
    Implementation of lightweight cryptographic primitives

    Implementation of lightweight cryptographic primitives by Hammad B.T., Jamil N., Rusli M.E., Z�Aba M.R., Ahmed I.T.

    Published 2023
    “…These classifications are very useful because the primitives have different and sometimes contrary characteristics. …”
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  20. 20
    Implementation of lightweight cryptographic primitives

    Implementation of lightweight cryptographic primitives by Hammad B.T., Jamil N., Rusli M.E., Z�Aba M.R., Ahmed I.T.

    Published 2023
    “…These classifications are very useful because the primitives have different and sometimes contrary characteristics. …”
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