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The Analysis of Proximity Between Subjects Based on Primary Contents Using Cosine Similarity on Lective

Al-rizki, Muhammad Andi and Wicaksono, Galih Wasis and Azhar, Yufis (2017) The Analysis of Proximity Between Subjects Based on Primary Contents Using Cosine Similarity on Lective. KINETIK, 2 (4). pp. 299-308. ISSN 2503-2259

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Abstract

In education world, recognizing the relationship between one subject and another is imperative. By recognizing the relationship between courses, performing sustainability mapping between subjects can be easily performed. Moreover, detecting and reducing any duplicated contents in several subjects will be also possible to execute. Of course, these conveniences will benefit lecturers, students and departments. It will ease the analysis and discussion processes between lecturers related to subjects in the same domain. In addition, students will conveniently choose a group of subjects they are interested in. Furthermore, departments can easily create a specialization group based on the similarity of the subjects and combine the courses possessing high similarity. In this research, given a good database, the relationship between subjects was calculated based on the proximity of the primary contents of the subjects. The feature used was term feature, in which value was determined by calculating TF-IDF (Term Frequency Inverse Document Frequency) from each term. In recognizing the value of proximity between subjects, cosine similarity method was implemented. Finally, testing was done utilizing precision, recall and accuracy method. The research results show that the precision and accuracy values are 90,91% and the recall value is 100%.

Item Type: Article
Keywords: TF-IDF, Cosine Similarity, Primary Content, Lective
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering > Department of Informatics (55201)
Depositing User: Yufis Azhar
Date Deposited: 31 Mar 2020 06:54
Last Modified: 31 Mar 2020 07:47
URI : http://eprints.umm.ac.id/id/eprint/60838

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