scholarly journals Uji Plagiarism pada Tugas Mahasiswa Menggunakan Algoritma Winnowing

2021 ◽  
Vol 2 (2) ◽  
pp. 108-112
Author(s):  
Moh Sadly Ramli ◽  
Sugiarto Cokrowibowo ◽  
Muh Fahmi Rustan
Keyword(s):  
Source Code ◽  
Plagiarism Detection ◽  
Average Value ◽  
Detection Systems

Plagiarism is the act of taking or plagiarizing the work, ideas or ideas of others either intentionally or unintentionally and claiming to be one's own work without mentioning the source or author. Often students plagiarize assignments given by the lecturer so that sometimes students just copy other people's assignments to complete the assignment. So that this can lead to dependence on other people in doing assignments and not being able to independently carry out assignments given by the lecturer. Currently, many plagiarism detection systems have been created to help reduce the level of plagiarism, one of which is the winnowing algorithm. In this study the authors used the winnowing algorithm to detect plagiarism in student assignments, namely programming source code, from the results of research conducted on 10 student assignments using the winnowing algorithm produced various similarity values as a percentage of similarity between two students tasks compared. With an average value of the overall similarity of the 10 tasks, namely 75.12%.

scholarly journals Online Judging Platform Utilizing Dynamic Plagiarism Detection Facilities

Computers ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 47
Author(s):  
Fariha Iffath ◽  
A. S. M. Kayes ◽  
Md. Tahsin Rahman ◽  
Jannatul Ferdows ◽  
Mohammad Shamsul Arefin ◽  
...  
Keyword(s):  
Source Code ◽  
Large Data ◽  
Large Data Sets ◽  
Detection Technique ◽  
Data Sets ◽  
Plagiarism Detection ◽  
Source Codes ◽  
Efficient Detection ◽  
Mathematical Problems ◽  
Automatic Scoring

A programming contest generally involves the host presenting a set of logical and mathematical problems to the contestants. The contestants are required to write computer programs that are capable of solving these problems. An online judge system is used to automate the judging procedure of the programs that are submitted by the users. Online judges are systems designed for the reliable evaluation of the source codes submitted by the users. Traditional online judging platforms are not ideally suitable for programming labs, as they do not support partial scoring and efficient detection of plagiarized codes. When considering this fact, in this paper, we present an online judging framework that is capable of automatic scoring of codes by detecting plagiarized contents and the level of accuracy of codes efficiently. Our system performs the detection of plagiarism by detecting fingerprints of programs and using the fingerprints to compare them instead of using the whole file. We used winnowing to select fingerprints among k-gram hash values of a source code, which was generated by the Rabin–Karp Algorithm. The proposed system is compared with the existing online judging platforms to show the superiority in terms of time efficiency, correctness, and feature availability. In addition, we evaluated our system by using large data sets and comparing the run time with MOSS, which is the widely used plagiarism detection technique.

scholarly journals “There must be Someone’s Name Under Every Bit of Text, Even if it is Unimportant or Incorrect”: Plagiarism as a Learning Strategy

2021 ◽  
Author(s):  
Beata Bielska ◽  
Mateusz Rutkowski
Keyword(s):  
Higher Education ◽  
Detection Rate ◽  
Learning Strategy ◽  
Plagiarism Detection ◽  
International Context ◽  
Detection Systems ◽  
Uniform Definition ◽  
Definition Of ◽  
Difficult Situations ◽  
Source Of Information

AbstractThe article offers analyses of the phenomenon of copying (plagiarism) in higher education. The analyses were based on a quantitative survey using questionnaires, conducted in 2019 at one of the Polish universities. Plagiarism is discussed here both as an element of the learning process and a subject of public practices. The article presents students’ definitions of plagiarism, their strategies for unclear or difficult situations, their experiences with plagiarism and their opinions on how serious and widespread this phenomenon is. Focusing on the non-plagiarism norm, that is the rule that students are not allowed to plagiarize, and in order to redefine it we have determined two strategies adopted by students. The first is withdrawing in fear of making a mistake (omitting the norm), which means not using referencing in unclear situations, e.g. when the data about the source of information are absent. The second is reducing the scope of the norm applicability (limiting the norm), characterized by the fact that there are areas where the non-plagiarism norm must be observed more closely and those where it is not so important, e.g. respondents classify works as credit-level and diploma-level texts, as in the credit-level work they “can” sometimes plagiarize since the detection rate is poor and consequences are not severe. The presented results are particularly significant for interpreting plagiarism in an international context (no uniform definition of plagiarism) and for policies aimed at limiting the scale of the phenomenon (plagiarism detection systems1).

Source Code Plagiarism Detection in an Educational Context: A Literature Mapping

2021 ◽  
Author(s):  
Rodrigo C Aniceto ◽  
Maristela Holanda ◽  
Carla Castanho ◽  
Dilma Da Silva
Keyword(s):  
Source Code ◽  
Educational Context ◽  
Plagiarism Detection ◽  
Literature Mapping

Plagiarism Detection Algorithm for Source Code in Computer Science Education

2015 ◽  
Vol 13 (4) ◽  
pp. 29-39 ◽  
Author(s):  
Xin Liu ◽  
Chan Xu ◽  
Boyu Ouyang
Keyword(s):  
Hash Function ◽  
Source Code ◽  
College Education ◽  
Detection Algorithm ◽  
Longest Common Subsequence ◽  
The Other ◽  
Plagiarism Detection ◽  
Detection Algorithms ◽  
Common Subsequence ◽  
Basic Concepts

Nowadays, computer programming is getting more necessary in the course of program design in college education. However, the trick of plagiarizing plus a little modification exists among some students' home works. It's not easy for teachers to judge if there's plagiarizing in source code or not. Traditional detection algorithms cannot fit this condition. The author designed an effective and complete method to detect source code plagiarizing according to the popular way of students' plagiarizing. There are two basic concepts of the algorithm. One is to standardize the source code via filtration against to remove the majority noises intentionally blended by plagiarists. The other one is an improved Longest Common Subsequence algorithm for text matching, using statement as the unit for matching. The authors also designed an appropriate HASH function to increase the efficiency of matching. Based on the algorithm, a system was designed and proved to be practical and sufficient, which runs well and meet the practical requirement in application.

A Comparison of Source Code Plagiarism Detection Engines

2004 ◽  
Vol 14 (2) ◽  
pp. 101-112 ◽  
Author(s):  
Thomas Lancaster ◽  
Fintan Culwin
Keyword(s):  
Source Code ◽  
Plagiarism Detection
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