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  1. 1
    Virtual reality in algorithm programming course: practicality and implications for college students

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
    “…The reliability of VR supports various variations in learning, including learning programming algorithms. …”
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  2. 2
    Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali

    Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

    Published 2025
    “…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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  3. 3
    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging

    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

    Published 2016
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  4. 4
    Text classification using Naive Bayes: An experiment to conference paper

    Text classification using Naive Bayes: An experiment to conference paper by Sainin, Mohd Shamrie

    Published 2005
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  5. 5
    Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad

    Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

    Published 2023
    “…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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  6. 6
    A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment

    A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment by Rajoo, S, Magalingam, P, Idris, NB, Samy, GN, Maarop, N, Shanmugam, B, Perumal, S

    Published 2024
    Proceedings Paper
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  7. 7
    Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad Kushairi

    Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad... by Ahmad, Nurul Atirah, Abu Samah, Khyrina Airin Fariza, Ahmad Kushairi, Nuwairah Aimi

    Published 2023
    “…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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  8. 8
    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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  9. 9
    Sentiment Analysis on Users' Satisfaction for Mobile Banking Apps in Malaysia

    Sentiment Analysis on Users' Satisfaction for Mobile Banking Apps in Malaysia by Misinem, ., Tri Basuki, Kurniawan, Mohd Zaki, Zakaria, Muhammad Aqil Azfar, Uzailee

    Published 2022
    “…The best accuracy result shows 94.37% by the Decision Tree algorithm, and Naïve Bayes obtained the worst outcome at 66%.…”
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  10. 10
    Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
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  11. 11
    Review of image denoising algorithms based on the wavelet transformation

    Review of image denoising algorithms based on the wavelet transformation by Khmag, Asem, Ramli, Abdul Rahman, Hashim, Shaiful Jahari, Syed Mohamed, Syed Abdul Rahman Al-Haddad

    Published 2013
    “…In spite of the sophistication of the recently methods, most algorithms have not yet attained a desirable level of applicability. …”
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  12. 12
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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  13. 13
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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  14. 14
    Analysing machine learning models to detect disaster events using social media

    Analysing machine learning models to detect disaster events using social media by Faris Azni Azlan, Mr.

    Published 2023
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  15. 15
    Text Summarization System with Bayesian Theorem on Oil & Gas Drilling Topic

    Text Summarization System with Bayesian Theorem on Oil & Gas Drilling Topic by Kurniawan, Iwan

    Published 2007
    “…In this project, Bayes theorem algorithm is studied and experimented by the implementation of a textual summarizer. …”
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  16. 16
    Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz

    Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz by Abdul Aziz, Azzatul Husna

    Published 2025
    “…The CRISP-DM methodology was followed to apply machine learning algorithms, namely Random Forest, Decision Tree, and Naive Bayes, to the data gathered in the library which is traffic, book rentals, and questionnaires. …”
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  17. 17
    Enhanced mechanism to handle missing data of Hadith classifier

    Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

    Published 2011
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  18. 18
    Comparison of machine learning classifiers for dimensionally reduced fMRI data using random projection and principal component analysis

    Comparison of machine learning classifiers for dimensionally reduced fMRI data using random projection and principal component analysis by Mohd Suhaimi, Nur Farahana, Htike, Zaw Zaw

    Published 2019
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  19. 19
    Fraud detection in shipping industry based on location using machine learning comparison techniques

    Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

    Published 2023
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  20. 20
    Sentiment analysis of customer review for Tina Arena Beauty

    Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

    Published 2025
    “…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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