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%.
Highlights
The effect of the pandemic era is that all learning uses online learning in web-based applications
The length of the title is processed by a text-mining algorithm and after that gives a weighting for each word in the title
Every title of file with weighting has a value that is calculated by Shared Nearest Neighbour (SNN) to get near the cluster for each category
Summary
The effect of the pandemic era is that all learning uses online learning in web-based applications. If online learning is an overload in the database, it makes a big problem that it can’t be accessed by all people The solving this problem is that if there is the same material with the same subject or topic, another teacher doesn’t need to upload it. The problem will be fixed by making an application to classify all of the material in online learning based on topic and subject with a specific category. The application uses a machine-learning algorithm to make classification by using the title of the file in the material in database online learning. Every title of file with weighting has a value that is calculated by SNN to get near the cluster for each category The utilization of this is a mobile application to know the accuracy of the algorithm and the result of classification. At the end of this research will be tested in a real database of online learning to get a real validation of the result of the application
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