z-logo
open-access-imgOpen Access
INTEGRASI ALGORITMA FISHER-YATES SEBAGAI PENGEMBANGAN E-LEARNING DI UNIT KEGIATAN BELAJAR MANDIRI
Author(s) -
Karisma Nanda Arditya,
Moh Bhanu Setyawan,
Adi Fajaryanto Cobantoro
Publication year - 2021
Publication title -
komputek
Language(s) - English
Resource type - Journals
eISSN - 2614-0985
pISSN - 2614-0977
DOI - 10.24269/jkt.v5i1.684
Subject(s) - computer science , mathematics education , e learning , learning management , educational institution , artificial intelligence , psychology , multimedia , educational technology , pedagogy
E-learning is currently very important and a must for educational institutions. Many e-learning application platforms are based on Learning Management System (LMS) that can be used by schools, whether they are open source, paid for or build their own applications. There are many considerations that must be faced when deciding to use an e-learning-based application (LMS) including infrastructure readiness, costs and application compatibility with the e-learning concept desired by educational institutions. The availability of features in the e-learning system is one that must be adjusted to the e- learning concept that will be selected. Each institution may be able to determine its own characteristics that can be specific and not yet fully accommodated in the e-learning application that currently exists. One of them is the feature to randomize exam questions to ensure that each student gets different questions with the same composition. This research will try to answer this problem by integrating the fisher-yates shuffel algorithm. The success of this algorithm integration will be assessed by conducting an exam simulation involving two classes and seeing how the system will randomly divide the exam questions to each student. The first assessment is the suitability of the composition of the questions and the similarity of the questions between students, the less students receive the same questions appearing on the exam questions, the better the system performance.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here