Determining Thesis Title using Winnowing Algorithm

This study presents the development and application of a system utilizing the winnowing algorithm to evaluate the suitability of thesis titles based on their relevance to existing research. By generating fingerprint values from input titles and calculating similarity percentages using Jaccard’s Similarity Coefficient, the system provides a quantitative measure of title uniqueness and originality. In this study, the similarity between the proposed title and existing titles was determined to be 38.4%, indicating a low level of overlap and confirming the title’s appropriateness for academic research. The winnowing algorithm enhances the efficiency and accuracy of the title selection process, reducing the risk of redundancy and plagiarism while ensuring alignment with academic standards. This automated approach streamlines decision-making, enabling students to choose focused and high-quality thesis topics. The system’s ability to deliver precise similarity metrics supports academic integrity and promotes originality in research. Future research could explore the integration of advanced algorithms or machine learning to further improve the system’s performance and adaptability across diverse academic domains.

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Publication Details

Journal
International Journal of Informatics Engineering and Computing
Published
2024-11-06
DOI
https://doi.org/10.70687/ijimatic.v1.i1.26
Primary Topic
Blockchain Technology in Education and Learning
Type
article
Field-Weighted Citation Impact
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article

Determining Thesis Title using Winnowing Algorithm

R Zainal Arifin Fandi Saputra, Indah Susilawati
International Journal of Informatics Engineering and Computing
Blockchain Technology in Education and Learning
article

Determining Thesis Title using Winnowing Algorithm

R Zainal Arifin Fandi Saputra, Indah Susilawati
article en

Abstract

This study presents the development and application of a system utilizing the winnowing algorithm to evaluate the suitability of thesis titles based on their relevance to existing research. By generating fingerprint values from input titles and calculating similarity percentages using Jaccard’s Similarity Coefficient, the system provides a quantitative measure of title uniqueness and originality. In this study, the similarity between the proposed title and existing titles was determined to be 38.4%, indicating a low level of overlap and confirming the title’s appropriateness for academic research. The winnowing algorithm enhances the efficiency and accuracy of the title selection process, reducing the risk of redundancy and plagiarism while ensuring alignment with academic standards. This automated approach streamlines decision-making, enabling students to choose focused and high-quality thesis topics. The system’s ability to deliver precise similarity metrics supports academic integrity and promotes originality in research. Future research could explore the integration of advanced algorithms or machine learning to further improve the system’s performance and adaptability across diverse academic domains.

International Journal of Informatics Engineering and ComputingVol. 1(1)
Universitas Mercu Buana Yogyakarta (ID)
Quality Education
Openalex Percentile: Top 69%
Blockchain Technology in Education and Learning
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