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  1. 1
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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  2. 2
    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
    “…Meanwhile, k-NN algorithm is used to classify the experimental data. …”
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  3. 3
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  4. 4
    Car recognition using Bayes Classifier / Nur Atiqah Mat Samadi

    Car recognition using Bayes Classifier / Nur Atiqah Mat Samadi by Mat Samadi, Nur Atiqah

    Published 2017
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  5. 5
    Naive bayes-guided bat algorithm for feature selection.

    Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

    Published 2013
    “…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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  6. 6
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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  7. 7
    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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  8. 8
    PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER

    PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER by Tay, Guo Hong

    Published 2019
    “…This is because both Naive Bayes and SVM are baseline algorithm used in text classification. …”
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    Final Year Project Report / IMRAD
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  9. 9
    Naive Bayes-guided bat algorithm for feature selection

    Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

    Published 2023
    “…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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  10. 10
    Utilize Medical Text Data to Estimate Disease Types by Using Naïve Bayes and ANN Classifier

    Utilize Medical Text Data to Estimate Disease Types by Using Naïve Bayes and ANN Classifier by Mujiono, Sadikin, Deshinta, Arrova Dewi, Purwanto S., Katijan, Ibrohim, Thohari

    Published 2021
    “…In this study, we address the medical unstructured data format by using Natural Language Processing approach. …”
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  11. 11
    Analyzing customer reviews for ARBA Travel using sentiment analysis

    Analyzing customer reviews for ARBA Travel using sentiment analysis by Abdullah, Nurulain

    Published 2025
    “…Three machine learning algorithms which are Naive Bayes, Logistic Regression, and Support Vector Machine, were implemented and evaluated using cross-validation and performance metrics such as accuracy, precision, recall, and F1- score. …”
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  12. 12
    Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki

    Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki by Maliki, Ahmad Firdaus

    Published 2021
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  13. 13
    Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin

    Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin by Mohd Adnin, Mohd Alief Mukhlis

    Published 2020
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  14. 14
    Text Categorization Using Naive Bayes Algorithm

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

    Published 2005
    “…The aims of this project are to categorize the textual document using naive Bayes algorithm and to measure the correctness of the chosen technique for the categorization process. …”
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  15. 15
    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
    “…The aims of this project are to categorize the textual document using naive Bayes algorithm and to measure the correctness of the chosen technique for the categorization process. …”
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    Conference or Workshop Item
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  16. 16
    Analysis of Sentiment Based on Opinions from the 2019 Presidential Election

    Analysis of Sentiment Based on Opinions from the 2019 Presidential Election by Nurul Adha Oktarini, Saputri, Misinem, ., Khoirul, Zuhri

    Published 2024
    “…The classification results on the test data demonstrated that the Naive Bayes Classifier algorithm achieved an overall accuracy of 71%. …”
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  17. 17
    A comparative analysis of machine learning algorithms for diabetes prediction

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…Nine features which are Age, Blood pressure, Skin thickness, Glucose, Diabetes pedigree function, Pregnancy, BMI, Insulin level, and Outcome been used for the prediction of diabetes. The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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  18. 18
    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…After the pre-processing stage in the data mining process, in the data classification stage, Support Vector Machines (SVM), Naive Bayes, Decision Trees, Artificial Neural Networks (ANN), Multilayer Perceptron (MLP), Logistic Regression (LR) algorithms have been used. …”
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  19. 19
    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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  20. 20
    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
    “…The algorithm used is using the LSTM algorithm, while the benchmarking that we tested is the Random Forest and Naive Bayes algorithm. …”
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