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  1. 1
    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
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    Thesis
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

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

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  7. 7
    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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  8. 8
    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory

    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory by Rusli, Julie Roslita

    Published 2011
    “…A user-friendly Graphical User Interface (GUI) is developed using Microsoft Visual Basic software to load and display the algorithm under test and display the result. …”
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  9. 9
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  10. 10
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…Subsequently, it is exploring into the development of random approaches based on MABSA, integrating components into others algorithm whereby Squirrel Search Algorithm (SSA), Cauchy Mutation (CM) approach, and Doppler Effect (DE) phenomenon. …”
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  11. 11
    Personality prediction using Random Forest algorithm / Wan Abdul Qayyum Abdul Wahab

    Personality prediction using Random Forest algorithm / Wan Abdul Qayyum Abdul Wahab by Abdul Wahab, Wan Abdul Qayyum

    Published 2023
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  12. 12
    Analysis and Modification of Grain - 128 Stream Cipher Algorithm

    Analysis and Modification of Grain - 128 Stream Cipher Algorithm by Norul Hidayah Lot@Ahmad Zawawi

    Published 2024
    thesis::master thesis
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  13. 13
    Algorithm for the legal regulation of internet financial crime

    Algorithm for the legal regulation of internet financial crime by Ambaras Khan, Hanna, Ab. Rahman, Suhaimi, Xinxin, Mao

    Published 2024
    “…To prevent crime, attention towards effective control of Internet finance crime has grown, emphasizing the protection of consumers’ rights, reduction of economic damage, and promotion of Internet finance development. Data processing for criminal acts on Internet finance platforms is crucial, with the utilization of random forest algorithms, including Decision tree and Bagging integration algorithms. …”
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  14. 14
    Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi

    Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi by Mohd Azmi, Nur Amirah

    Published 2025
    “…Traditional methods struggle to model these complexities effectively, necessitating adoption of advanced algorithms to improve accuracy. The aim of this project is to develop a Diamond Price Prediction System using Random Forest, designed to accurately predict diamond prices based on attributes. …”
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  15. 15
    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network by Puteri Azwa, Ahmad

    Published 2014
    “…The EVFA approach can relocate the sensor nodes using a repulsive and attractive force after initial deployment and CS algorithm is more efficient in exploring the search of maximum coverage area in random deployment. …”
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  16. 16
    ABC: android botnet classification using feature selection and classification algorithms

    ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

    Published 2017
    “…The Information Gain algorithm is used to select the most significant permissions, then the classification algorithms Naïve Bayes, Random Forest and J48 used to classify the Android apps as botnet or benign apps. …”
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  17. 17
    Predicting customer churn in telecommunication service provider industry using Random Forest / Wan Muhammad Naqib Zafran Wan Roslan

    Predicting customer churn in telecommunication service provider industry using Random Forest / Wan Muhammad Naqib Zafran Wan Roslan by Wan Roslan, Wan Muhammad Naqib Zafran

    Published 2023
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  18. 18
    A fault syndromes simulator for random access memories

    A fault syndromes simulator for random access memories by Wan Hasan, Wan Zuha, Abdul Halim, Izhal, Mohd Sidek, Roslina, Othman, Masuri

    Published 2008
    “…At present, the March test algorithm is used to detect and diagnose all faults related to Random Access Memories. …”
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  19. 19
    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli

    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

    Published 2017
    “…Framework development methodology is used to make sure the prototype is successfully developed according to the schedule. …”
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  20. 20
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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