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  1. 1
    The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)

    The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA) by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Samsudin, Ruhaidah, Ameerbakhsh, Omair

    Published 2021
    “…This study proposes a machine learning model that applies a combination of sentiment-based support vector machine that is optimized by the whale optimization algorithm for predicting the daily price of a digital currency. …”
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  2. 2
    Suicide and self-harm prediction based on social media data using machine learning algorithms

    Suicide and self-harm prediction based on social media data using machine learning algorithms by Abdulrazak Yahya, Saleh, Fadzlyn Nasrini, Mostapa

    Published 2023
    “…In combined with robust machine learning algorithms, social networking data may provide a potential path ahead. …”
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  3. 3
    Enhancing loan approval decision-making: an interpretable machine learning approach using LightGBM for digital economy development / Teuku Rizky Noviandy, Ghalieb Mutig Idroes and Irsan Hardi

    Enhancing loan approval decision-making: an interpretable machine learning approach using LightGBM for digital economy development / Teuku Rizky Noviandy, Ghalieb Mutig Idroes and... by Noviandy, Teuku Rizky, Idroes, Ghalieb Mutig, Hardi, Irsan

    Published 2024
    “…This study aims to enhance loan approval decision-making in the digital economy using an interpretable machine learning approach. …”
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  4. 4
    Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques

    Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques by Lim, Shi Ru

    Published 2022
    “…This study attempted to predict mental health disorders among Twitter users using machine learning techniques. Support Vector Machine (SVM), Decision Tree, and Nave Bayes are three examples of machine learning approaches applied in this study. …”
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  5. 5
    The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework

    The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework by Normi Sham Awang, Abu Bakar, Norzariyah, Yahya, Norbik Bashah, Idris, Engku Rabiah Adawiah, Engku Ali, Jasni, Mohamad Zain, Erni Eliana, Khairuddin, Ahmad Firdaus, Zainal Abidin, Murtaj, Sheikh Mohammad Tahsin, Siti Sarah, Maidin

    Published 2024
    “…The overall CentralBank Digital Currency Project Index (CBDCPI) was selected as a target variable,while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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  6. 6
    Machine learning based return prediction for digital financial portfolios

    Machine learning based return prediction for digital financial portfolios by LinXi Shi, Thien Sang Lim, Jin Yan, Pengcheng Qi, Tao Li

    Published 2025
    “…The machine learning algorithm is introduced to optimize the digital financial portfolio investment return prediction system. …”
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  7. 7
    The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework

    The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework by Awang Abu Bakar, Normi Sham, Yahya, Norzariyah, Idris, Norbik Bashah, Engku Ali, Engku Rabiah Adawiah, Mohamad Zain, Jasni, Khairuddin, Erni Eliana, Zainal Abidin, Ahmad Firdaus, Murtaj, Sheikh Mohammad Tahsin, Maidin, Siti Sarah

    Published 2024
    “…The overall Central Bank Digital Currency Project Index (CBDCPI) was selected as a target variable, while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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  8. 8
    Improving hand written digit recognition using hybrid feature selection algorithm

    Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

    Published 2022
    “…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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  9. 9
    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
    “…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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  10. 10
    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions

    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

    Published 2023
    “…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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  11. 11
    A systematic review of machine learning techniques and applications in soil improvement using green materials

    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
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  12. 12
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  13. 13
    A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science

    A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

    Published 2021
    “…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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  14. 14
    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets

    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

    Published 2021
    “…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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  15. 15
    A systematic review of machine learning techniques and applications in soil improvement using green materials

    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
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  16. 16
    A review unveiling various machine learning algorithms adopted for biohydrogen productions from microalgae

    A review unveiling various machine learning algorithms adopted for biohydrogen productions from microalgae by Mohamad Zulfadhli Ahmad Sobri, Alya Redhwan, Fuad Ameen, Lim, Jun Wei, Liew, Chin Seng, Mong, Guo Ren, Hanita Daud, Rajalingam Sokkalingam, Ho, Chii-Dong, Anwar Usman, D. H. Nagaraju, Pasupuleti Visweswara Rao

    Published 2023
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  17. 17
    Recognize Hate Speech On Twitter Using Machine Learning

    Recognize Hate Speech On Twitter Using Machine Learning by Yashaswini, Kini, Chitra, K, Harilakshmi, V.M.

    Published 2024
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  18. 18
    Detecting Malware with Classification Machine Learning Techniques

    Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

    Published 2023
    “…The following research report focuses on the implementation of classification machine learning methods for detecting malware. The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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  19. 19
    Detecting Malware with Classification Machine Learning Techniques

    Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

    Published 2023
    “…The following research report focuses on the implementation of classification machine learning methods for detecting malware. The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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  20. 20
    RENTAKA: A novel machine learning framework for crypto-ransomware pre-encryption detection

    RENTAKA: A novel machine learning framework for crypto-ransomware pre-encryption detection by S. M. M Yassin, S. M. Warusia Mohamed, Abdollah, Mohd Faizal, Mohd, Othman, Ariffin, Aswami

    Published 2022
    “…This experiment included five widely used machine learning classifiers: Naïve Bayes, kNN, Support Vector Machines, Random Forest, and J48. …”
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