Emotion Detection based on Column Comments in Material of Online Learning using Artificial Intelligence. - Repositori Universitas Negeri Malang

Emotion Detection based on Column Comments in Material of Online Learning using Artificial Intelligence.

Wahyono, Irawan Dwi and Saryono, Djoko and Putranto, Hari and Asfani, Khoirudin and Rosyid, Harits Ar and Mohamad, Mohd Murtadha and Said, Mohd Nihra Haruzuan Bin Mohamad and Horng, Gwo Jiun and Shih, Jia-Shing (2022) Emotion Detection based on Column Comments in Material of Online Learning using Artificial Intelligence. International Journal of Interactive Mobile Technologies 16 (3), 2022.

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Abstract

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%.

Item Type: Article
Subjects: L Education > LB Theory and practice of education > LB2300 Higher Education
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Sastra (FS) > Laporan Karya Ilmiah FS
Depositing User: Users 2 not found.
Date Deposited: 29 Apr 2022 06
Last Modified: 23 Mar 2022 03:10
URI: http://repository.um.ac.id/id/eprint/196719

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