ANALISIS TINGKAT PLAGIASI DOKUMEN SKRIPSI DENGAN METODE COSINE SIMILARITY DAN PEMBOBOTAN TF-IDF

Plagiarism is the activity of duplicating or imitating the work of others then recognized as his own work without the author's permission or listing the source. Plagiarism or plagiarism is not something that is difficult to do because by using a copy-paste-modify technique in part or all of the document, the document can be said to be the result of plagiarism or duplication. The practice of plagiarism occurs because students are accustomed to taking the writings of others without including the source of origin, even copying in its entirety and exactly the same. Plagiarism practices are mostly carried out by students, especially when completing the final project or thesis One way that can be used to prevent the practice of plagiarism is by doing prevention and detecting. Plagiarism detection uses the concept of similarity or document similarity is one way to detect copy & paste plagiarism and disguised plagiarism. one of the right methods that can be done to detect plagiarism by analyzing the level of document plagiarism using the Cosine Similarity method and the TF-IDF weighting. This research produces an application that is able to process the similarity value of the document to be tested. Hasik testing shows that it is appropriate between manual calculations and implementation of algorithms in the application made. Use of the Literature Library is quite effective in the Stemming process. Calculations that use stemming will have a higher similarity value compared to calculations without stemming methods.

Forensic Linguistics function in Evidentiary and Investigative Contexts

the main aim of this paper is to provide insights into the vital role of FL in Evidentiary and Investigative Contexts. the paper contains many segments; Authorship analysis and attribution, Plagiarism Detection, Speaker identification, and voice comparison, Language as evidence in civil cases (Trademark, Brand name Law, Defamation).

Peer review declaration

All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single-blind Each submitted paper reviewed by two minimum of reviewers after meet the minimum criteria. The review based on the following aspects: 1) Technical Criteria (Scientific merit, Clarity of expression, and Sufficient discussion of the context of the work, and suitable referencing); 2) Quality Criteria (Originality, Motivation, Repetition, Length); and 3) presentation criteria (Title, Abstract, Diagram, figures, tables and captions, Text and mathematics, and Conclusion). We also used iThenticate for plagiarism detection. • Conference submission management system: Easychair • Number of submissions received: 125 • Number of submissions sent for review: 117 • Number of submissions accepted: 90 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 90/125 = 72% • Average number of reviews per paper: 2 Reviewers • Total number of reviewers involved: 36 • Any additional info on review process: No • Contact person for queries: Name : Dr. Anita Ahmad Kasim Affiliation: Universitas Tadulako, Indonesia Email : [email protected]

Uji Plagiarism pada Tugas Mahasiswa Menggunakan Algoritma Winnowing

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%.

Cross-Platform Binary Code Homology Analysis Based on GRU Graph Embedding

Binary code homology analysis refers to detecting whether two pieces of binary code are compiled from the same piece of source code, which is a fundamental technique for many security applications, such as vulnerability search, plagiarism detection, and malware detection. With the increase in critical vulnerabilities in IoT devices, homology analysis is increasingly needed to perform cross-platform vulnerability searches. Existing methods for cross-platform binary code homology detection usually convert binary code to instruction sequences and do semantic embedding of the sequences as if they were natural language. However, the gap between natural language and binary code is large, and the spatial features of the binary code are easily lost by directly comparing the semantics. In this paper, we propose a GRU-based graph embedding method to compare the homology of binary functions. First, the attribute control flow graph (ACFG) is built for the assembly function, then the GRU-based graph embedding neural network is used to generate the embedding vector for the ACFG, and finally the homology of the binary code is determined by calculating the distance between the embedding vectors. The experimental results show that our method greatly improves the detection accuracy of negative samples compared with Gemini, the latest method based on graph embedding binary code similarity detection.

Academics Perceptions of Electronic Resources at the University of Venda, South Africa

This study examined the perceptions of academic researchers regarding electronic resources (e-resources) provided by the library at the University of Venda (UNIVEN), South Africa. The quantitative research approach and survey research design were adopted to conduct the investigation. Data was collected using a self-administered structured questionnaire randomly distributed to 45 UNIVEN academics. The findings of this study revealed that although academics at UNIVEN find e-resources easy to use, believe the resources improve academic performance, and frequently encouraged postgraduate students to use them, the majority of them had plagiarism concerns and were only moderately satisfied with available e-resources at UNIVEN. This study recommends that the university library should train academics on plagiarism detection. In addition, the library should adopt innovative ways of improving e-resource services, such as providing an Online Public Access Catalogue (OPAC) with advanced and federated search capabilities.