The objective of this study is to depict teacher competence in creating educational materials within the independent curriculum at primary schools. This research employs a qualitative descriptive approach and utilizes both primary and secondary data sources. Data gathering methods consist of observations and interviews. The outcomes of the study of the research can be found that teacher competence in compiling learning tools in the independent curriculum can be described through five aspects, namely: 1) The teacher's knowledge aspect which discusses teaching ability and mastery of the material. 2) Aspects of teacher skills related to student interaction and involvement in preparing learning tools and their learning styles. 3) Attitude and behavioral aspects where the role of the teacher is crucial in establishing an effective and conducive learning atmosphere and is able to facilitate the student learning process. 4) The context aspect is associated with enhancing teacher professionalism and the use of technology as a learning support tool. 5) The evaluation aspect is related to developing student assessments and measuring understanding with rubric assessments.

Background: Iterative Reconstruction (IR) method was first applied to CT in 1960 and successfully used for the first time in clinical research by reconstructing 128 x 128 images according to image metrics and using high-resolution images of 512 x 512 for special research activities such as image evaluation. artifacts and noise. In 2008, the development of IR can improve image quality and reduce the amount of radiation in clinical CT diagnosis. Iterative reconstruction promises to improve image quality while reducing radiation dose. This has been demonstrated in CT of the thorax, coronary arteries, abdomen, spine and neck, paranasal sinuses, and head. Sinogram-Afirmed Iterative Reconstruction (SAFIRE) is one of the iterative algorithm reconstruction methods that uses noise modeling techniques, Sinogram-Afirmed Iterative Reconstruction (SAFIRE), promises to improve Cranial CT (CCT). In this new technique, raw data-based iteration for artifact reduction is combined with image-based iteration using smooth regularization that estimates the variance of image noise in various directions at each image pixel and adjusts it with a spatial variance regularization function simultaneously. Methods: This study is a literature review, where literature exploration is carried out on various databases with keywords such as, Reference sources used in compiling this article include google scollar, as well as articles in English and Indonesian scientific journals. Results: Itarative Reconstruction (IR) Head CT Scan, SAFIRE includes reducing or adding noise to the image results, artifacts, acquisition time, increasing SNR and CNR and reducing dose in the examination. Conclusion: Analysis of Safire results in Head CT-Scan Imaging has an Itarative Reconstruction (SAFIRE) procedure, the role of safire in head CT scans is to optimize noise in the Reconstructed image and can reduce artifacts in the image and increase SNR, CNR in the Reconstructed results so that it can provide better information.