Selected Papers from the 1st International Conference on Islam, Science and Technology, ICONISTECH-1 2019, 11-12 July 2019, Bandung, Indonesia

Research Article

Improving The Detection of Plagiarism in Scientific Articles Using Machine Learning Approaches

Download610 downloads
  • @INPROCEEDINGS{10.4108/eai.11-7-2019.2297759,
        author={Muhammad Agreindra Helmiawan and Irfan  Fadil and Dwi  Yuniarto and Fathoni  Mahardika and Fidi  Supriadi},
        title={Improving The Detection of Plagiarism in Scientific Articles Using Machine Learning Approaches},
        proceedings={Selected Papers from the 1st International Conference on Islam, Science and Technology, ICONISTECH-1 2019, 11-12 July 2019, Bandung, Indonesia},
        publisher={EAI},
        proceedings_a={ICONISTECH-1},
        year={2020},
        month={11},
        keywords={machine learning detection plagiarism algorithm},
        doi={10.4108/eai.11-7-2019.2297759}
    }
    
  • Muhammad Agreindra Helmiawan
    Irfan Fadil
    Dwi Yuniarto
    Fathoni Mahardika
    Fidi Supriadi
    Year: 2020
    Improving The Detection of Plagiarism in Scientific Articles Using Machine Learning Approaches
    ICONISTECH-1
    EAI
    DOI: 10.4108/eai.11-7-2019.2297759
Muhammad Agreindra Helmiawan1,*, Irfan Fadil1, Dwi Yuniarto1, Fathoni Mahardika1, Fidi Supriadi1
  • 1: STMIK Sumedang
*Contact email: agreindra@stmik-sumedang.ac.id

Abstract

One of the modern problems that occur in the current research and publication process is the duplication of the results of other people's research that is presented again by other parties. With the ease of the resources obtained, the more open the opportunity to bring up a problem called Plagiarism. This is attempted to be completed by the computer system with new approaches to detect and predict the existence of plagiarism in research automatically. In this article, approaches and methods for detecting plagiarism use machine learning techniques, where machine learning is empowered to become an algorithm as construction and evaluation in detecting plagiarism. Technically, this algorithm will compare and analyze the compatibility of words and sentences in documents with other document databases so that the analysis becomes an evaluation material, prediction, and determination that the document is plagiarism or not. The purpose of this study is to protect intellectual property and ideas, as well as the results to improve better performance and level of accuracy in detecting plagiarism.