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  1. 1
    Extended spatial decision tree algorithm for classifying hotspot occurrence

    Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

    Published 2013
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  2. 2
    A decision tree based on spatial relationships for predicting hotspots in peatlands

    A decision tree based on spatial relationships for predicting hotspots in peatlands by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2014
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  3. 3
    An extended ID3 decision tree algorithm for spatial data

    An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2011
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  4. 4
    State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm

    State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm by Lipu M.S.H., Ayob A., Saad M.H.M., Hussain A., Hannan M.A., Faisal M.

    Published 2023
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  5. 5
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  6. 6
    Classification model for hotspot occurrences using spatial decision tree algorithm

    Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…This study describes the application of data mining technique namely decision tree on forest fires data. …”
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  7. 7
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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    Monograph
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  8. 8
    An efficient scalable batch-rekeying scheme for secure multicast communication using multiple logical key trees

    An efficient scalable batch-rekeying scheme for secure multicast communication using multiple logical key trees by Zakaria, Omar, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina

    Published 2014
    “…Instead of using only a single key tree multiple key trees are used and at the end of each batch time the algorithm decides which tree will be used to update the keys. …”
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  9. 9
    SEDF: a spoofed email detection framework employed by a lightweight web browser plug-in for detecting the spoofed email / Al Ya@Geogiana Buja...[et al.]

    SEDF: a spoofed email detection framework employed by a lightweight web browser plug-in for detecting the spoofed email / Al Ya@Geogiana Buja...[et al.] by Buja, Al Ya@Geogiana, Ahmad, Illiasaak, Zolkeply, Mohd Syafiq

    Published 2014
    “…The method used to detect fake e-mail is by tracing back the email header. …”
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    Research Reports
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  10. 10
    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves

    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

    Published 2023
    “…At the early infection stage, it is very difficult to diagnose the disease because infected trees do not exhibit any symptoms. Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
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  11. 11
    Phishing attack detection using machine learning method

    Phishing attack detection using machine learning method by Jupin, John Arthur

    Published 2019
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    Undergraduates Project Papers
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  12. 12
    Modeling forest fires risk using spatial decision tree

    Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

    Published 2011
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  13. 13
    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms

    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

    Published 2016
    “…The User Profile Filter (UPF) was proposed to aid the SVM algorithm to classify the captured traffics into normal and abnormal behavior. …”
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  14. 14
    FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems

    FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems by Alansi, M., Elshafiey, I., Al-Sanie, A., Mabrouk, A.

    Published 2016
    “…Robust multi-user detection (MUD) methods based on space division multiple access (SDMA) techniques are essential to efficiently exploit the electromagnetic spectrum. …”
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  15. 15
    Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS

    Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS by Akbari, M., Reza, A.W., Noordin, K.A., Manesh, M.R., Hindia, M.N.

    Published 2014
    “…Cooperative spectrum sensing (CSS) in cognitive radio (CR) has been widely investigated to be considered as a spectrum scanning mechanism that allows secondary users or cognitive radio users (SUs) to use detected spectrum holes caused by primary users (PUs) absence. …”
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  16. 16
    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…This research presents a mobile malware static detection method based on Naive Bayes. The approach aims to offer a solution to protect users from potential threats such as Banking Trojan malware. …”
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  17. 17
    Keylogger detection analysis using machine learning algorithm / Muhammad Faiz Hazim Abdul Rahman

    Keylogger detection analysis using machine learning algorithm / Muhammad Faiz Hazim Abdul Rahman by Abdul Rahman, Muhammad Faiz Hazim

    Published 2022
    “…Besides, to test the accuracy of detection models on keylogger dataset comparing two machine learning algorithms. …”
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  18. 18
    Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance

    Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance by Akbari, M., Reza, A.W., Noordin, K.A., Dimyati, K., Manesh, M.R., Hindia, M.N.

    Published 2016
    “…In cognitive radio (CR), cooperative spectrum sensing (CSS) has been extensively explored to be accounted for in a spectrum scanning method that permits secondary users (SUs) or cognitive radio users to utilize discovered spectrum holes caused by the absence of primary users (PUs). …”
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  19. 19
    An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition

    An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition by Mohd. Hasbullah, Omar

    Published 2011
    “…In order to use the algorithm effectively, users need to balance between detection accuracy and execution time. …”
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  20. 20
    Classification model for hotspot occurrences using a decision tree method

    Classification model for hotspot occurrences using a decision tree method by Sitanggang, Imas Sukaesih, Ismail, Mohd Hasmadi

    Published 2011
    “…This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
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