Search Results - (( develop commerce intention algorithm ) OR ( java automatic classification algorithm ))

  • Showing 1 - 4 results of 4
Refine Results
  1. 1

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
    Get full text
    Get full text
    Thesis
  2. 2

    A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

    Published 2019
    “…It consists of 3-stage procedures: feature ranking, feature selection and classification. Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3

    Consumers' intention to use e-money mobile using the decomposed theory of planned behavior by Husnil, Khatimah

    Published 2016
    “…The Partial Least Squares Method (PLS) series PLS 2.0 M3 for algorithm and bootstrap techniques and SPSS 18 was used to test the hypothesis that has been developed. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    From AI to Experience How Personalization Shapes Online Shopping Journeys in E-Marketplaces by Raeni Dwi, Santy, Yoga, Wicaksana, Mohammad Fauzil, Adhim

    Published 2025
    “…This study, titled “From AI to Experience: How Personalization Shapes Online Shopping Journeys in E-Marketplaces in Indonesia”, aims to analyze the role of artificial intelligence (AI)–driven personalization in influencing consumer behavior, satisfaction, and loyalty in digital marketplaces. Using the recent development of social commerce integration into e-commerce, particularly the merger of TikTok and Tokopedia, as a contextual backdrop, the research highlights how recommendation algorithms, chatbots, and personalized content contribute to consumer decision-making processes. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article