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  1. 1
    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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  2. 2
    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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  3. 3
    Network monopoly / Tan Kean Yeap

    Network monopoly / Tan Kean Yeap by Tan , Kean Yeap

    Published 2002
    “…Moreover, because of the expanding memory anda processing power of these computers, users can put the machine to work on new kinds of applications and functions. …”
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  4. 4
    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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  5. 5
    Efficient kerberos authentication scheme for cross-domain systems in industrial internet of things using ECC

    Efficient kerberos authentication scheme for cross-domain systems in industrial internet of things using ECC by Ismail, Haqi Khalid

    Published 2021
    “…The offline scheme utilizes a Time-based One-Time Password (TOTP) algorithm to allow users to authenticate to the vehicle without needing an Internet connection once they have registered online when Internet access is available. …”
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  6. 6
    Phishing attack detection using machine learning method

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

    Published 2019
    “…This is because some of the computer users do not install security system in their computer. …”
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  7. 7
    Estimating Depressive Tendencies Of Twitter User Via Social Media Data

    Estimating Depressive Tendencies Of Twitter User Via Social Media Data by Loh, Hooi Teng

    Published 2023
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  8. 8
    Review of the machine learning methods in the classification of phishing attack

    Review of the machine learning methods in the classification of phishing attack by Jupin, John Arthur, Sutikno, Tole, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Deris, Stiawan

    Published 2019
    “…However, in widely using this computer network, the privacy of computer users is in danger, especially for computer users who do not install security systems in their computer. …”
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  9. 9
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The key is the trigger mechanism to the algorithm. Until the advent of the Internet, encryption was rarely used by the public, but was largely a military tool. …”
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    Final Year Project
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  10. 10
    Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset

    Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset by Afiefah Hannani, Abdul Halim

    Published 2023
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  11. 11
    Extreme learning machine for user location prediction in mobile environment

    Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

    Published 2011
    “…This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. …”
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  12. 12
    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. This study is carried out through the utilisation of two machine learning techniques, namely Decision Tree and Naive Bayes, on Jupyter Notebook in order to conduct an analysis of the Keylogger Detection dataset obtained from a trustworthy website known as Kaggle. …”
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  13. 13
    Automatic email classification system / Phang Siew Ting

    Automatic email classification system / Phang Siew Ting by Phang , Siew Ting

    Published 2003
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  14. 14
    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms

    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

    Published 2021
    “…In virtualization, a physical server changes into the virtual machine (VM) and acts as a physical server. Due to the large number of users sometimes the task sent by the user to cloud causes the VM to be under loaded or overloaded. …”
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  15. 15
    Music Recommender System Using Machine Learning Content-Based Filtering Technique

    Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

    Published 2022
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  16. 16
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  17. 17
    A power saver scheduling algorithm using DVFS and DNS techniques in cloud computing data centres

    A power saver scheduling algorithm using DVFS and DNS techniques in cloud computing data centres by Atiewi S., Yussof S., Rusli M.E.B., Zalloum M.

    Published 2023
    “…Cloud computing; Costs; Dynamic frequency scaling; Electric power utilization; Energy efficiency; Energy utilization; Infrastructure as a service (IaaS); Network security; Quality of service; User interfaces; Virtual machine; Voltage scaling; Cloud computing environments; Data centres; DVFS; Dynamic voltage frequency scaling; Energy-Efficient Scheduling; Low energy consumption; Reduce energy consumption; Task-scheduling algorithms; Green computing…”
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  18. 18
    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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  19. 19
    ROA-CONS: raccoon optimization job scheduling

    ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

    Published 2021
    “…An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. …”
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  20. 20
    Extreme learning machine for user location prediction in mobile environment

    Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

    Published 2011
    “…This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. …”
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