Clustering Diagnostic Assessment of Students with the K-Means Algorithm Based on Talents and Interests

Mesra Yel, Syahril Efendi, Muhammad Zarlis, Saib Suwilo

2023

Abstract

E-Learning is a way of teaching and learning online in virtual classrooms which gives experiences, changes and needs according to technological developments and new learning paradigms with the flexibility given to educators in formulating learning designs and assessments. This research contributes to producing a student classification model using the k-means clustering algorithm to be applied to differentiated e-learning, which can accommodate all user needs according to abilities, interests, and talents by using artificial intelligence. The result is a differentiated e-learning model is produced to classify diagnostic assessments. Based on test data on 20 students, it was successfully classified into 3 clusters, namely students in class 1 with a trend of X values being in the do not know the value, Y with a very ignorant value while the Y value is in a value between not knowing and partially understanding with a total of 9 people. Students are in grade 3 with a trend with a value of X being between not knowing and partial understanding, Y with a partially understanding value, while the Y value is at a very ignorant value with a total of 6 people with an accuracy level of f1 test score 100%.

Paper Citation

in Harvard Style

Yel M., Efendi S., Zarlis M. and Suwilo S. (2023). Clustering Diagnostic Assessment of Students with the K-Means Algorithm Based on Talents and Interests. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 295-301. DOI: 10.5220/0012457200003848

in Bibtex Style

@conference{icaisd23,
author={Mesra Yel and Syahril Efendi and Muhammad Zarlis and Saib Suwilo},
title={Clustering Diagnostic Assessment of Students with the K-Means Algorithm Based on Talents and Interests},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD},
year={2023},
pages={295-301},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012457200003848},
isbn={978-989-758-678-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD
TI - Clustering Diagnostic Assessment of Students with the K-Means Algorithm Based on Talents and Interests
SN - 978-989-758-678-1
AU - Yel M.
AU - Efendi S.
AU - Zarlis M.
AU - Suwilo S.
PY - 2023
SP - 295
EP - 301
DO - 10.5220/0012457200003848
PB - SciTePress