AN IMPROVED TECHNIQUE FOR ANALYZING SIMILARITY INDEX USING TURNITIN

Abstract

The detection of plagiarism by software in the checking of a student plagiarized document in higher institutions of
learning (universities and colleges) plays a crucial role in preventing plagiarism amongst students. However,
plagiarism detection services show a variation by violating the intellectual property rights of the students during the
detection process. A control framework was developed, according to the legal requirement that protects intellectual
property to protect the integrity of authors in the course of the plagiarism detection. Students’ documents submitted
to their lecturers were pre-processed. The framework filtered at least two letter words using python programming
language and subjected and to see the extent of locating plagiarized sources in respect of the original thesis. An
accuracy of about 70% was obtained from results obtained using Turnitin. The control framework prevented the
violation of intellectual property by the use of the pre-processed thesis during the plagiarism detection process by a
third party such as Turnitin. There is an encouragement in academic skilled writing and beyond in academia as every
undertaking is the property of the owner. The control framework is, therefore, a preventive marker for the violation
of intellectual property.