Search Results - (( its application bayes algorithm ) OR ( _ application mining algorithm ))*

Refine Results
  1. 1

    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%.…”
    Get full text
    Get full text
    Get full text
    Article
  2. 2
  3. 3
  4. 4

    Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

    Published 2025
    “…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    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. …”
    Get full text
    Get full text
    Student Project
  6. 6

    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. …”
    Get full text
    Get full text
    Thesis
  7. 7
  8. 8
  9. 9

    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. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Efficient prime-based method for interactive mining of frequent patterns. by Mohammad Hossein, Nadimi Shahraki, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2011
    “…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
    Get full text
    Get full text
    Article
  12. 12

    Clustering algorithm for market-basket analysis : the underlying concept of data mining technology by Abdul Kadir, Khairil Annuar

    Published 2003
    “…The author used a data mining software called PolyAnalyst 4.5 to perform analysis on the set of items that customers have bought in supermarket for market-basket application. …”
    Get full text
    Get full text
    Thesis
  13. 13
  14. 14

    Modifying iEclat algo ithm for infrequent patterns mining by Julaily Aida, Jusoh, Mustafa, Man

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15
  16. 16
  17. 17

    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.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  18. 18

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…The enormous of information on the World Wide Web makes it obvious candidate for data mining research. Application of data mining techniques to the World Wide Web referred as Web mining where this term has been used in three distint ways; Web Content Mining, Web Structure Mining and Web Usage Mining. …”
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19
  20. 20

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Moreover, this study introduces a mining algorithm called PC-miner to mine the mining model frequently with various values of minsup. …”
    Get full text
    Get full text
    Thesis