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All Journal Kalbiscientia Jurnal Sains dan Teknologi
Felix Aristo
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Industrial & Manufacturing Engineering Mechanical Engineering

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Pengembangan Fitur Analisis Data dan Visualisasi Informasi pada E-Learning Moodle Felix Aristo; Samosir, Ridha Sefina
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 11 No. 02 (2024): Jurnal Sains dan Teknologi
Publisher : Research and Community Service INSTITUT TEKNOLOGI DAN BISNIS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbiscientia.v11i02.4341

Abstract

Moodle is an E-Learning media that is open source or can be further developed as needed. PT GML Performance Consulting used Moodle for training or workshops for its partner companies. Based on the current use of Moodle, there are features that need to be added to support the training or workshop activities. This research aims to develop data analysis and information visualization features in Moodle as additional features. The addition of features to Moodle will be formatted as a plug-in using the prototyping method. The data analysis technique used for the addition of features is a clustering technique using the K-Means algorithm. Testing on the development of the Moodle E-Learning system using the black box testing methodology.
Pengembangan Fitur Analisis Data dan Visualisasi Informasi pada E-Learning Moodle Felix Aristo; Samosir, Ridha Sefina
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 11 No. 02 (2024): Jurnal Sains dan Teknologi
Publisher : Research and Community Service UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbiscientia.v11i02.4341

Abstract

Moodle is an E-Learning media that is open source or can be further developed as needed. PT GML Performance Consulting used Moodle for training or workshops for its partner companies. Based on the current use of Moodle, there are features that need to be added to support the training or workshop activities. This research aims to develop data analysis and information visualization features in Moodle as additional features. The addition of features to Moodle will be formatted as a plug-in using the prototyping method. The data analysis technique used for the addition of features is a clustering technique using the K-Means algorithm. Testing on the development of the Moodle E-Learning system using the black box testing methodology.
Co-Authors Ridha Sefina Samosir