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  1. 1
    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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  2. 2
    Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic

    Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic by Jiao, BianBian, Leelavathi, R., Lohgheswary, N., Nopiah, Z. M.

    Published 2022
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  3. 3
    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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  4. 4
    Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection

    Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

    Published 2024
    “…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. The application of GA for data dimensionality reduction from 41,140 to 20,769 features, coupled with fitness evaluation based on SVM, resulted in an observed increase in accuracy by 8.10% for SVM, 36.1% for Naïve Bayes, 7.82% for LSTM, 5.47% for DNN, and 6.25% for CNN. …”
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  5. 5
    Non invasive stress detection method based on discrete wavelet transform and machine learning algorithms

    Non invasive stress detection method based on discrete wavelet transform and machine learning algorithms by Altaf, Hunain, Ibrahim, Siti Noorjannah, Funke Olanrewaju, Rashidah

    Published 2021
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  6. 6
    Uncovering user perceptions toward digital banks in Indonesia: A Naïve Bayes sentiment analysis of twitter data

    Uncovering user perceptions toward digital banks in Indonesia: A Naïve Bayes sentiment analysis of twitter data by Karmagatri, Mulyani, Aziz, Clarisa Fezia Amanda, Asih, Wini Rizki Purnama, Jumbri, Isma Addi

    Published 2023
    “…The subsequent stages involved classification using the Naïve Bayes algorithm and word cloud visualization to identify the most commonly used words based on user responses. …”
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  7. 7
    Text Categorization Using Naive Bayes Algorithm

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

    Published 2005
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  8. 8
    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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  9. 9
    Stock market turning points rule-based prediction / Lersak Photong … [et al.]

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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  10. 10
    GA-based feature subset selection in a spam/non-spam detection system

    GA-based feature subset selection in a spam/non-spam detection system by Behjat, Amir Rajabi, Mustapha, Aida, Nezamabadi-pour, Hossein, Sulaiman, Md. Nasir, Mustapha, Norwati

    Published 2012
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  11. 11
    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
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  12. 12
    Comparison of Naïve bayes classifier with back propagation neural network classifier based on f - folds feature extraction algorithm for ball bearing fault diagnostic system

    Comparison of Naïve bayes classifier with back propagation neural network classifier based on f - folds feature extraction algorithm for ball bearing fault diagnostic system by Osman Mohamed Addin, Addin, Salit, Mohd Sapuan, Othman, Mohamed, Ahmed Ali, Basheer Ahmed

    Published 2011
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  13. 13
    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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  14. 14
    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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  15. 15
    A Naïve-Bayes classifier for damage detection in engineering materials

    A Naïve-Bayes classifier for damage detection in engineering materials by Addin, O., Salit, Mohd Sapuan, Mahdi Ahmad Saad, Elsadig, Othman, Mohamed

    Published 2007
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  16. 16
    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
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  17. 17
    Applying learning to filter text

    Applying learning to filter text by Sainin, Mohd Shamrie

    Published 2005
    “…Text filtering has been a successful application especially in e-mail filtering. The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
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  18. 18
    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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  19. 19
    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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  20. 20
    Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri

    Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri by Ahmad Bakri, Alia Hannani

    Published 2024
    “…The study focuses on developing a divorce prediction system using the Naive Bayes algorithm, a widely used classifier. The system achieved 98% accuracy in predicting divorce based on a comprehensive dataset. …”
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