Penilaian Tingkat Pengetahuan Siswa Dalam Sistem e-Learning Menggunakan Machine Learning - Yovi Pratama; Yuga Pramudya; Evan Albert; Mumtaz Ilham Syafatullah; Rio Ferdinand; Verwin Juniansyah; Errissya Rasywir (Forum Kerjasama Pendidikan Tinggi (FKPT), 2022)
Data clustering provides an overview of the grouping of data through classification so that the groups have levels that have the same category. Cluster classification is carried out on agricultural data in Jambi Province with agricultural production groups including rice, rubber, palm oil, and coffee in the period 2021 for 11 (eleven) cities/districts including Jambi City, East Tanjung Jabung Regency, Sungai Full City, Kerinci Regency, Muaro Jambi Regency, West Tanjung Jabung Regency, Merangin Regency, Sarolangun Regency, Batanghari Regency, Tebo Regency, and Bungo Regency. The purpose of the cluster is used for allocations related to the budget, land, and support that can be used both to increase the amount of production and evaluation related to agriculture, especially at the Jambi Province level. So that the clustering carried out using the Weka application is 4 clusters, the result is that the cluster process stops at the 2nd iteration, the output information that occupies cluster 0 is 3 cities/districts, cluster 1 has 1 city/regency, cluster 2 has 2 cities/districts, and cluster 3 there are 5 cities/districts, with a total attribute of 11 (eleven) city/district data. Based on experiments on manual clustering, it can be concluded that the equations that can be seen from the output results using Weka and manual calculations are the same as doing two data iterations and with the same data group results.