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Journal : International Journal of Informatics Engineering and Computing

Determining Thesis Title using Winnowing Algorithm Saputra, Rendi; Susilawati, Indah
International Journal of Informatics Engineering and Computing Vol. 1 No. 1 (2024): International Journal of Informatics Engineering and Computing
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/ijimatic.v1.i1.26

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.
Expert System to Determine Camera Price Using VIKOR Method Purwanto, Hendri; Susilawati, Indah
International Journal of Informatics Engineering and Computing Vol. 1 No. 1 (2024): International Journal of Informatics Engineering and Computing
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/ijimatic.v1.i1.27

Abstract

This study presents the design and implementation of an expert system for determining the best camera recommendations for beginners, utilizing a web-based platform to deliver tailored results based on user input. The VIKOR method is employed to evaluate and rank camera products, ensuring optimal recommendations by balancing multiple criteria such as technical specifications, usability, and cost-effectiveness. Analysis of five camera products revealed that the Fujifilm X-A5 achieved the lowest VIKOR value of 0, indicating it as the top recommendation for beginners. The system's calculations were validated against manual computations, achieving a 100% accuracy rate, and thereby confirming the reliability of the expert system. The proposed system not only enhances decision-making efficiency but also significantly reduces the time required for experts to rank and evaluate multiple camera products. This approach demonstrates the potential of integrating multi-criteria decision-making methods into expert systems to provide accurate, user-centric recommendations in real time.