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Image of PENGARUH ABSTRACT SYNTAX TREE PADA SISTEM DETEKSI KEMIRIPAN KODE SUMBER MENGGUNAKAN ALGORITMA RATCLIFF/OBERSHELP

Text

PENGARUH ABSTRACT SYNTAX TREE PADA SISTEM DETEKSI KEMIRIPAN KODE SUMBER MENGGUNAKAN ALGORITMA RATCLIFF/OBERSHELP

Sholeh, Muhammad - Personal Name;

Penilaian

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Penilaian anda saat ini :  

In today’s technological era, source code has become something that is mostly written. Among the diversity of existing programming source code, many of them are the result of acts of plagiarism. Process of detecting plagiarism in the source code is not an easy to do. Based on the information above, this research uses the Abstract Syntax Tree method because of its ability to determine the structure of a source code which is then represented by tokens. The Ratcliff/Obershelp algorithm was chosen to perform similarity calculations based on the token structure of the source code. The data used in this study amounted to 25 source code documents with details of 5 main source code documents and 20 modified source code documents. The results of this study indicate that the Abstract Syntax Tree method affects the calculation of the similarity of the source code, and also the developed system can detect the similarity of the source code using the Ratcliff/Obershelp algorithm.


Availability
Inventory Code Barcode Call Number Location Status
2207000711T67641T676412022Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T676412022
Publisher
Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022
Collation
xvi, 65 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
003.107
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Jurusan Teknik Informatika
Identifikasi Sistem
Specific Detail Info
-
Statement of Responsibility
SEPTA
Other version/related

No other version available

File Attachment
  • PENGARUH ABSTRACT SYNTAX TREE PADA SISTEM DETEKSI KEMIRIPAN KODE SUMBER MENGGUNAKAN ALGORITMA RATCLIFF/OBERSHELP
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