Conference paper 2021

Weight Term Document in Clustering Algorithm for Classification a Final Project in Online Learning

2021 International Research Symposium On Advanced Engineering and Vocational Education, IRSAEVE 2021
Conference · pp. 1-4
Abstract

The problem in all online learning is that all assessment such as final project is uploaded in it and lecture must evaluate all final project in a specific course that has different topics and subjects so it makes difficult for the lecture. This research built an application that makes a classification of final project documents from the student based on the same subjects and topics. The application takes data from database online learning in a specific course that the database of the final project has a different scope and broad topic. Classification is carried out based on the similarity of topics from the final project document for certain subjects. The document is in the form of text, so a text-mining algorithm is needed to determine some of the topics contained in the final project document. Determination of the final project document according to a particular topic requires a similarity algorithm. This research takes the final project file from Google Drive and the online learning database and implements it in a mobile application. The average result of testing is that the accuracy is 72.49%. © 2021 IEEE.

Keywords

Author Keywords

mobile application classification text-mining

Index Keywords

E-learning Online learning Data mining Digital storage Clustering algorithms Database systems Text processing Mobile applications Student-based Text-mining Mobile computing Google+ Information retrieval systems Learning database Mining algorithms Project documents Project file Similarity algorithm
Author Affiliations
Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia
Universitas Negeri Malang, Malang, East Java, Indonesia
Funding & Acknowledgements
No funding information
References 10 References
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