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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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  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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  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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  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
    Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School

    Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

    Published 2021
    “…The Computational Thinking results of quantitative data were collected using pre-test and post-test that consisted of five subjective computational thinking items. …”
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  9. 9
    Critical review of computational thinking in Islamic studies

    Critical review of computational thinking in Islamic studies by Nazir, Faridah, Jano, Zanariah, Idrus, Azean Idruwani

    Published 2026
    “…While Computational Thinking (CT) enhances research efficiency through natural language processing (NLP) and data-driven approaches, its implementation risks algorithmic reductionism and loss of interpretive depth in sacred texts. …”
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  10. 10
    Enhancing understanding of programming concepts through physical games

    Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

    Published 2017
    “…The activities were conducted involving first and fourth year undergraduate students and Master students in Programming 1 (31 students), Data Structure (6 students), Analysis of Algorithm (12 students) and Advanced Algorithm (22 students) courses respectively. …”
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  11. 11
    Mathematical modelling on communication between two parties / Nor Anees Asyiqin Md Disa, Khairunnisa Munawarah Khairul Anwar and Aniesa Farhana Mazlan

    Mathematical modelling on communication between two parties / Nor Anees Asyiqin Md Disa, Khairunnisa Munawarah Khairul Anwar and Aniesa Farhana Mazlan by Md Disa, Nor Anees Asyiqin, Khairul Anwar, Khairunnisa Munawarah, Mazlan, Aniesa Farhana

    Published 2022
    “…Since the key exchange process is successful, we think the offered methods are effective.…”
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  12. 12
    Art-Integration in Computational Thinking as an Unplugged Pedagogical Approach at A Rural Sarawak Primary School

    Art-Integration in Computational Thinking as an Unplugged Pedagogical Approach at A Rural Sarawak Primary School by Nur Hasheena, Anuar, Fitri Suraya, Mohamad, Jacey Lynn, Minoi

    Published 2020
    “…The purpose of this study is to explore the use of visual art in learning the problem-solving process and as an unplugged approach to involve learners in computational thinking. …”
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  13. 13
    An empirical study of TensorFlow lite performances in Raspberry Pi / Mohamad Harith Mohd Zahid

    An empirical study of TensorFlow lite performances in Raspberry Pi / Mohamad Harith Mohd Zahid by Mohd Zahid, Mohamad Harith

    Published 2020
    “…Thus, it can be concluded that as the processing data increase the time average decrease but vice versa to the different types of models where it increases with the more data it processes over time.…”
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  14. 14
    Predicting game-induced emotions using EEG, data mining and machine learning

    Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

    Published 2024
    “…The data acquisition stage, data pre-processing, data annotation and feature extraction stage were designed and conducted in this paper to obtain and extract the EEG features from the Gameemo dataset. …”
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  15. 15
    What, how and when to use knowledge in neural network application

    What, how and when to use knowledge in neural network application by Wan Ishak, Wan Hussain, Abdul Rahman, Shuzlina

    Published 2004
    “…The methodology comprises five steps namely variable selection, data collection, data preprocessing, training &validation, and testing.…”
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  16. 16
    Predicting STEM academic performance in secondary schools: data mining approach

    Predicting STEM academic performance in secondary schools: data mining approach by Termedi @Termiji, Mohammad Izzuan, Ab. Jalil, Habibah

    Published 2019
    “…Three different data mining classification algorithms which are Decision Tree (DT), Artificial Neural Networks (ANN), and Naive Bayes (NB) will be used on the dataset. …”
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  17. 17
    Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph

    Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph by Joseph, Corina

    Published 2023
    “…The rapid progress of AI has been facilitated by the extensive use of other technologies like machine learning methods for structured data, modern deep learning, and natural language processing for unstructured data. …”
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  18. 18
    Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction

    Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction by Muna Elsadig, Ashraf Osman Ibrahim Elsayed, Shakila Basheer, Manal Abdullah Alohali, Sara Alshunaifi, Haya Alqahtani, Nihal Alharbi, Wamda Nagmeldin

    Published 2022
    “…Then, the natural language processing (NLP) algorithm was applied to the unique data column and extracted a huge number of useful data features in terms of meaningful text information. …”
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  19. 19
    Prediction of mental health among university students

    Prediction of mental health among university students by Sahlan, Fadhluddin, Hamidi, Faris, Misrat, Muhammad Zulhafizal, Adli, Muhammad Haziq, Wani, Sharyar, Gulzar, Yonis

    Published 2021
    “…This paper explores the state of student well-being and uses various machine learning algorithms for the prediction process based on the data of entrepreneurial competency in university students. …”
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  20. 20
    AMI screening using linguistic fuzzy rules

    AMI screening using linguistic fuzzy rules by Ainon, R.N., Bulgiba, Awang, Lahsasna, A.

    Published 2010
    “…Since there is a tradeoff in the fuzzy system between the accuracy which measures the capability of the system to predict the diagnosis of AMI and transparency which reflects its ability to describe the symptoms-diagnosis relation in an understandable way, the proposed fuzzy rules are designed in a such a way to find an appropriate balance between these two conflicting modeling objectives using multi-objective genetic algorithms. The main advantage of the generated linguistic fuzzy rules is their ability to describe the relation between the symptoms and the outcome of the diagnosis in an understandable way, close to human thinking and this feature may help doctors to understand the decision process of the fuzzy rules.…”
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