<![CDATA[Sexual violence on campus, particularly at Politeknik Negeri Lhokseumawe, is an issue that requires serious attention and effective handling. To improve the current manual complaint management system, the application of information technology through the K-Means Clustering method is necessary for the prevention and complaint system of sexual violence. This approach is expected to assist in grouping complaint data from victims, making it easier to identify levels of sexual violence and to design more targeted responses. This research was conducted by developing and managing a sexual violence complaint system, where the complaints were grouped into three clusters based on the calculation of the data. The clusters were validated using the silhouette method, resulting in a score of 0.50 for cluster 0 (moderate level), 0.20 for cluster 1 (moderate level), and 0.58 for cluster 2 (low level). These results indicate that the K-Means Clustering method is effective in categorizing complaint data and can support more effective handling of sexual violence cases on campus.]]>
Copyrights © 2025
