Penerapan Algoritma K-Means Clustering Pada Tingkat Penyelesaian Pendidikan Di Provinsi Indonesia - Akhmad Basalamah; Resad Setyadi (Universitas Samudra, 2023)
The level of educational attainment plays a crucial role in the progress of a country, as higher levels of education achieved have a positive impact on the development of the nation. The data used in this research is obtained from the Indonesian Central Bureau of Statistics (BPS), which is a reliable and authoritative source of statistical information in the country. The objective of this study is to conduct data mining analysis and examine the educational attainment levels across 34 provinces in Indonesia based on education levels and provinces from 2020 to 2022. The analysis process is performed using RapidMiner Data Mining software. The findings of this study include the mapping of education levels and provinces into specific clusters. The method applied is K-Means, a data mining technique used for classifying data with the aim of identifying patterns or groups within it. In this research, cluster mapping is divided into three groups: high cluster (K0), medium cluster (K1), and low cluster (K2). For elementary school (SD) level, there are 29 high clusters, 4 medium clusters, and 1 low cluster. For junior high school (SMP) level, there is 1 high cluster province, 20 medium clusters, and 13 low clusters. It is hoped that the information derived from the research findings has the potential to provide a deeper understanding and valuable insights as a comprehensive overview of the educational attainment levels in Indonesian provinces over the past few years, aiming to enhance the quality of education in Indonesia.