2021
DOI: 10.37385/jaets.v2i2.210
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Product Codefication Accuracy With Cosine Similarity And Weighted Term Frequency And Inverse Document Frequency (TF-IDF)

Abstract: In the SiPaGa application, the codefication search process is still inaccurate, so OPD often make mistakes in choosing goods codes. So we need Cosine Similarity and TF-IDF methods that can improve the accuracy of the search. Cosine Similarity is a method for calculating similarity by using keywords from the code of goods. Term Frequency and Inverse Document (TFIDF) is a way to give weight to a one-word relationship (term). The purpose of this research is to improve the accuracy of the search for goods codifica… Show more

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Cited by 6 publications
(11 citation statements)
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“…𝑑𝑓 𝑑 = |{𝑑 ∈ 𝐷 ∢ 𝑑 ∈ 𝑑}| is the number of documents containing term t and 𝑁 is the total number of documents in the corpus, N = |D|. Adding 1 to avoid dividing by 0 if 𝑑𝑓 𝑑 is not present in the corpus [25].…”
Section: Feature Extraction For Machine Learning Algorithmsmentioning
confidence: 99%
“…𝑑𝑓 𝑑 = |{𝑑 ∈ 𝐷 ∢ 𝑑 ∈ 𝑑}| is the number of documents containing term t and 𝑁 is the total number of documents in the corpus, N = |D|. Adding 1 to avoid dividing by 0 if 𝑑𝑓 𝑑 is not present in the corpus [25].…”
Section: Feature Extraction For Machine Learning Algorithmsmentioning
confidence: 99%
“…1. Case folding: Case folding is performed to convert all characters in the text to lowercase for uniformity [5]. 2.…”
Section: Text Preprocessingmentioning
confidence: 99%
“…In addition, this research also refers to the implementation of TF-IDF weighting and cosine similarity algorithms in the SiPaGa application [5], which has provided a strong foundation for the current research focusing on applying these algorithms in the tourism destination article search feature. By applying the TF-IDF and Cosine Similarity algorithms to the tourism destination article search feature, the current research aims to enhance the accuracy and relevance of the search results for tourism destination articles.…”
Section: Introductionmentioning
confidence: 99%
“…Digital Image Processing or what is often called digital image processing is a field of science that studies how an image is formed, processed, and analyzed so as to produce information that can be understood by humans. This study aims to utilize the field of digital image processing in helping humans in everyday life to produce information that is easy to understand(Rifki Kosasih, 2021;Sintia et al, 2021) Several studies have been conducted to prove the accuracy of the Hue Saturation Value (HSV) feature using the K-Nearest Neighbor method. In a study conducted by (Nafiah, 2019) in "Classification of Maturity of Mangoes Based on HSV Image with KNN" on the accuracy results generated from testing the testing data obtained in the manga test has an average accuracy value of 55% with a distance between K=1-10.…”
Section: Introductionmentioning
confidence: 99%