Penerapan Algoritma Fuzzy C-Means untuk Analisis Tingkat Pendidikan Sekolah Dasar di Karanganyar - Daffa Rizki Putra Noordi; Irfan Agus Prastowo; Nadia Amalia Putri; Zariel Ardian Ekovih; Dwi Hartanti (Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta, 2023)
The use of the Fuzzy C-Means (FCM) algorithm is an interesting topic in the analysis of elementary school education. Karanganyar is an area that has many elementary schools and we need a method that can classify data with high accuracy to understand elementary school data effectively. Therefore, this study aims to apply the FCM algorithm in data mining to analyze elementary schools in Karanganyar. The research began by collecting data on elementary schools in Karanganyar which included attributes such as the number of study groups and students. The FCM method is then used to process the data. The data clustering technique is enabled by this algorithm. Experimental findings indicate that the application of FCM algorithm in data mining to analyze an elementary school in Karanganyar produces information grouping. In rapidminer's calculations, 6 clusters were obtained, namely cluster 0 consisting of 45 elementary schools with the lowest educational level category, cluster 1 consisting of 3 elementary schools with the highest educational level category, cluster 2 consisting of 73 elementary schools with the lowest educational level category, cluster 3 consisting of 14 elementary schools with the higher education level category, cluster 4 consisting of 39 elementary schools with various levels of education categories, cluster 5 consisting of 27 elementary schools with the medium education level category. The DBI value acquired by the FCM method is -0.471, and since this number is near to 0, it can be argued that the cluster that the algorithm generated is excellent. This can help the government and the educational system. in formulating sensible development plans and policies. Karanganyar's educational system.