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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Danno, Bayissa Leta
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Analysis of similarity index between iThenticate and Ouriginal plagiarism detection software: a comprehensive study Rahman, Md. Hamidur; Danno, Bayissa Leta; Wase Mola, Dessalegn; Islam, Muhammad Shahidul; Hussain Andrabi, Syed Murtaza; Reza, Md. Nasim; Shaw, Dhananjoy
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 3: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i3.pp2096-2104

Abstract

Intellectual property plagiarism is increasingly prominent in contemporary society, involving the unethical practice of claiming someone else's ideas, words, or creative works without proper acknowledgment. This study aimed to compare the performance of iThenticate and Ouriginal plagiarism detection software by analyzing their similarity index. Twenty original manuscripts (N=20) were examined for content similarity, with each manuscript analyzed first with Ouriginal and then with iThenticate. The focus was on comparing the two tools based on matched sources, word matches, and overall similarity index percentage. Data analysis using SPSS v26 included descriptive statistics, an independent t-test, correlation, and ranking of the similarity percentages, with significance set at p<0.05. The results indicated no significant differences in matching sources, matching words, or similarity index (p>0.05) between iThenticate and Ouriginal. A strong positive correlation (r=.758, p<.000) was observed between the similarity indices of the two software programs. The analysis of the low similarity range (≤10%) also revealed no statistical significant difference (p>.05). However, the mean similarity percentage detected by iThenticate was higher at 11.40%, compared to 6.85% for Ouriginal. Based on the findings, both iThenticate and Ouriginal demonstrated comparable effectiveness in detecting plagiarism, highlighting their importance in curbing academic dishonesty and protecting intellectual property rights.
Co-Authors Hussain Andrabi, Syed Murtaza Islam, Muhammad Shahidul Rahman, Md. Hamidur Reza, Md. Nasim Shaw, Dhananjoy Wase Mola, Dessalegn