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In the era of globalization, university graduates are required to have the ability to implement knowledge in real practice, which is realized through the Field Work program. This study aims to evaluate the compliance of Task Force reporting at PT PLN (Persero) North Sumatra Main Distribution Unit (UID North Sumatra). The method used is a quantitative approach with K-Means Clustering. Compliance reporting data was obtained from internal company documents, which then went through the preprocessing and clustering stages using the K-Means algorithm, with the determination of the optimal cluster number through the Elbow and Silhouette methods. The K-Means clustering analysis results identified two groups of units with different levels of compliance. Cluster 2, consisting of UP3 Binjai and UP3 Sibolga, showed a higher and more consistent level of reporting compliance. In contrast, Cluster 1 (including UP2D, UP3 B. Barisan, UP3 L. Pakam, UP3 Medan, UP3 Medan Utara, UP3 Nias, UP3 P. Sidimpuan, UP3 P. Siantar, and UP3 Prapat) had a tendency for lower compliance. This finding indicates a difference in reporting consistency that affects the effectiveness of work safety supervision. The K-Means method is proven to help PLN management identify units with low compliance, allowing corrective actions to be prioritized appropriately.

This project is motivated by the high risk of work accidents in the concrete production process, especially at night when there is poor lighting. Based on observations, there were various significant work incidents, such as injuries from sharp objects and being caught in heavy equipment, which indicate the need for increased risk control. This study aims to design personal protective equipment in the form of an innovative safety helmet using the Job Safety Analysis (JSA) method to improve occupational safety and health (K3) at PT Adhi Persada Beton Batching Plant Kebonarum. The methodology used includes hazard identification, risk analysis, and solution development in the form of designing a safety helmet that is adjusted to the ergonomic needs of workers. This study also includes analysis of work accident data, identification of potential hazards, and evaluation of the effectiveness of existing personal protective equipment. The results of the study indicate that the application of the JSA method can identify risks in a more structured manner, as well as produce recommendations for safety helmet innovations that can improve worker protection against potential hazards.