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  1. 1
    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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  2. 2
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
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    Thesis
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  3. 3
    Tracking student performance in introductory programming by means of machine learning

    Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

    Published 2023
    “…Big data; Decision trees; Education computing; Learning algorithms; Learning systems; Machine learning; Smart city; Students; Trees (mathematics); Educational data mining; Educational institutions; Hidden patterns; Introductory programming; Introductory programming course; Student performance; Student's performance; Weka; Data mining…”
    Conference Paper
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  4. 4
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Finding a good classification algorithm is an important component of many data mining projects. …”
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  5. 5
    Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm

    Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm by Lee, Angela Siew Hoong *, Zuraini Zainol, Ng, Claudia, Chan, Khin Whai

    Published 2019
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  6. 6
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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    Monograph
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  7. 7
    Building customer churn prediction models in Indonesian telecommunication company using decision tree algorithm

    Building customer churn prediction models in Indonesian telecommunication company using decision tree algorithm by Ramadhanti,, Darin, Larasati, Aisyah, Muid, Abdul, Mohamad, Effendi

    Published 2023
    “…This study uses data mining techniques with decision tree algorithms to predict customer churn in one of Indonesian Telecommunication companies. …”
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  8. 8
    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
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  9. 9
    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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  10. 10
    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan

    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

    Published 2013
    “…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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  11. 11
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  12. 12
    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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  13. 13
    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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  14. 14
    An efficient and effective case classification method based on slicing

    An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

    Published 2006
    “…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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  15. 15
    Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip

    Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip by Mohd Taip, Muhammad Saifullah

    Published 2023
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  16. 16
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  17. 17
    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
    “…Initially, this tool adopts only Crow Search, Jaya, and Sine Cosine algorithms. …”
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  18. 18
    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining

    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

    Published 2025
    “…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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  19. 19
    Towards a better feature subset selection approach

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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  20. 20
    Propositional satisfiability method in rough classification modeling for data mining

    Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

    Published 2002
    “…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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