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  1. 1
    Text Categorization Using Naive Bayes Algorithm

    Text Categorization Using Naive Bayes Algorithm by Wan Hazimah, Wan Ismail

    Published 2005
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  2. 2
    A Data Mining Approach to Construct Graduates Employability Model in Malaysia

    A Data Mining Approach to Construct Graduates Employability Model in Malaysia by Myzatul Akmam Sapaat, Aida Mustapha, Johanna Ahmad, Khadijah Chamili, Rahamirzam Muhamad

    Published 2024
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  3. 3
    Text categorization using naive bayes algorithm

    Text categorization using naive bayes algorithm by Wan lsmail @ W. Abdullah, Wan Hazimah, Kamaruddin, Siti Sakira, Sainin, Mohd Shamrie

    Published 2006
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  4. 4
    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour

    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

    Published 2022
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  5. 5
    A data mining approach to construct graduates employability model in Malaysia

    A data mining approach to construct graduates employability model in Malaysia by Sapaat, Myzatul Akmam, Mustapha, Aida, Ahmad, Johanna, Chamili, Khadijah, Muhamad, Rahamirzam

    Published 2011
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  6. 6
    Unravel parking difficulty via relative chain code algorithm / Chan Huey Min

    Unravel parking difficulty via relative chain code algorithm / Chan Huey Min by Chan , Huey Min

    Published 2005
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  7. 7
    Sentiment analysis on airline reviews using Naive Bayes / Nurul Sarah Aliessa Che Harun

    Sentiment analysis on airline reviews using Naive Bayes / Nurul Sarah Aliessa Che Harun by Che Harun, Nurul Sarah Aliessa

    Published 2025
    “…In the design and implementation phases, TF-IDF was considered in cleaning and preparing the reviews for application, while the construction of a sentiment analysis model was implemented through the use of the Multinomial Naive Bayes algorithm. …”
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  8. 8
    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
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  9. 9
    A benchmark of modeling for sentiment analysis of the Indonesian Presidential Election in 2019

    A benchmark of modeling for sentiment analysis of the Indonesian Presidential Election in 2019 by Hulliyah, Khodijah, Awang Abu Bakar, Normi Sham, Ismail, Amelia Ritahani, M. Octaviano, Pratama

    Published 2020
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  10. 10
    Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment

    Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment by Babakura, Abba, Sulaiman, Md Nasir, Mustapha, Norwati, Kasmiran, Khairul A.

    Published 2014
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  11. 11
    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier

    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah, Noorizan , Yahya

    Published 2013
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  12. 12
    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat

    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
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  13. 13
    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction

    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

    Published 2024
    “…Therefore, a fuzzy model based on machine learning and data mining is a vital solution. …”
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  14. 14
    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
    “…The dataset is split into training and testing sets to develop the Naive Bayes (NB) model. The NB model achieved a commendable accuracy of 89.8%, indicating good performance in classifying potential job applicants. …”
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  15. 15
    Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes

    Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes by Wiliani, Ninuk, T.K.A, Rahman, Ramli, Suzaimah

    Published 2024
    “…Statistical criteria, including recall, specificity, and area under the curve (AUC), are employed to assess model performance. The findings indicate that the GNB algorithm surpasses BNB, with a mean average precision (mAP) of 39.83% with an 85:15 training-test ratio, whereas BNB reaches a maximum mAP of 29.25% at a 90:10 ratio. …”
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  16. 16
    Cyberbullying detection: a machine learning approach

    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…This model combines a rule-based approach of sentiment analysis and a supervised machine learning algorithm to classify the text. …”
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  17. 17
    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
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  18. 18
    A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis

    A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis by Mohammed Nadir bin Ali

    Published 2024
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  19. 19
    Daily rainfall prediction using clonal selection algorithm

    Daily rainfall prediction using clonal selection algorithm by Noor Rodi, Nur Syazwani, Ismail , Amelia Ritahani, Abdul Malik, Marlinda

    Published 2012
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  20. 20
    Predicting Customer Behaviour on Buying Life Insurance using Machine Learning

    Predicting Customer Behaviour on Buying Life Insurance using Machine Learning by Fabu Ayub A Ghafar, Norhana Abd Rahim, Yumn Suhaylah Yusoff

    Published 2026
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