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Shared Nearest Neighbour in Text Mining for Classification Material in Online Learning Using Mobile Application
Author(s) -
Irawan Dwi Wahyono,
Djoko Saryono,
Hari Putranto,
Khoirudin Asfani,
Harits Ar Rosyid,
Sunarti Sunarti,
Mohd Murtadha Mohamad,
Mohd Nihra Haruzuan Mohamad Said,
Gwo Jiun Horng,
Jia-Shing Shih
Publication year - 2022
Publication title -
international journal of interactive mobile technologies (ijim)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 16
ISSN - 1865-7923
DOI - 10.3991/ijim.v16i04.28991
Subject(s) - computer science , artificial intelligence , big data , subject (documents) , machine learning , online learning , mobile device , data mining , multimedia , world wide web
There are many resources for media learning in online learning that all of the teachers made many media which it made a problem if there have the same subject and material. This problem made online learning having a big database and many materials made useless because the material has the same purpose. The big problem in overload database is that online learning can't be accessed by everyone. This research to fix this problem developed an algorithm in Artificial Intelligence for the classification of material in online learning with the same subject and purpose so that teachers can use already media. This algorithm is text mining and Shared Nearest Neighbour (SSN) that is embedded in the mobile application to display the classification and the location of searching media in database online learning. The testing in this research  applied in 142 media  with 130 data training and 12 data testing is  the result of testing is 94,7% of the accuracy of the algorithm  and The average of validation is 73,33%.

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