Cluster Analysis Using K-Means Algorithm and Fuzzy C- Means Clustering For Grouping Students' Abilities In Online Learning Process

Indah Purnama Sari (Universitas Muhammadiyah Sumatera Utara, Indonesia)
Al-Khowarizmi Al-Khowarizmi (Universitas Muhammadiyah Sumatera Utara)
Ismail Hanif Batubara (Universitas Muhammadiyah Sumatera Utara)

Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE)
Vol 2, No 1 (2021)

The time of the Covid-19 pandemic, which is still unknown when it will end, has resulted in the learning and teaching process having to be carried out online. The impact of the learning process carried out online is a less satisfactory result than the learning process carried out offline. This study aims to group students based on their learning outcomes in statistics courses and measured probability based on the variables of attendance scores, assignments, midterm exams (UTS), and final semester exams (UAS) which are then used to evaluate learning for subjects that require analytical skills. good quantitative. This study uses cluster k-means analysis and fuzzy C-Means in grouping students into three groups based on their learning outcomes. After being grouped,