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All Journal Journal of Dinda : Data Science, Information Technology, and Data Analytics
Ibnu Faisal
Universitas Islam Negeri Sumatera Utara
Computer Science & IT

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Shoe Damage Identification System Using the Cosine Method in Web-Based K2n Store Ibnu Faisal; Raissa Amanda Putri
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v5i1.1795

Abstract

This research aims to develop a Web-Based Shoe Damage Identification System in K2N Store using the Rapid Application Development (RAD) methodology and the Cosine Similarity method. This system is designed to help the process of automatically identifying shoe damage based on the description of the symptoms that the user inputs. There are several main menus in this system, namely Login, Damage, Symptoms, and Case Base, each of which supports an effective flow of damage and symptom data management. The Login menu is used for user authorization, while the Crash and Symptoms menu allows for the management of data on crash types and related symptoms. The Case Base menu serves as the main reference in the identification process with the Cosine method, where the system calculates the degree of similarity between the new damage description and the existing reference data. Based on the test results, this system is able to provide accurate damage identification results, taking into account the similarity of the symptom description mathematically. The use of the Cosine method in RAD has proven to be effective in producing a fast and flexible solution for K2N Store Stores. Thus, this system is expected to increase efficiency and accuracy in the process of identifying shoe damage, as well as provide better service to customers.
Co-Authors Raissa Amanda Putri