Analysis of The Characteristics of Teachers With High Internet Self-Efficacy Levels using The K-Means Algorithm

The purpose of this study was to see the readiness of teachers in conducting online learning. The characteristics of the teachers collected in this study were gender, generation, last education, teacher tenure, learning environment and variations of online learning models. This study uses the K-Means algorithm for clustering. The dataset used in this study were 96 junior high school teachers in Central Java who had a high level of internet self-efficacy. The dataset of teachers who have a high level of internet self-efficacy is obtained from the results of data analysis on 285 junior high school teachers, who have varying levels of internet self-efficacy, both high, medium and low. The results of the K-Means analysis obtained 8 clusters with various characteristics of each cluster. The data attributes analyzed were gender, generation, last education, teacher tenure, learning environment and variations of online learning models. The results showed that in all data clusters were dominated by female gender with a bachelor's educational background. Meanwhile, the relatively more dominant characters in all clusters are generation X data, teacher tenure between 11 and 20 years, a supportive learning environment, and data on the use of varied learning models.