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In a national-scale educational assessment system, such as the National Examination, the need for several sets of questions that have the same level of difficulty is very required to avoid cheating by students. Therefore, the objective, which is to make a set of questions with the same level of difficulty automatically, is done in this research. It used a machine learning approach, namely K-Means. To achieve this goal, several following procedures need to be implemented. Firstly, we need to create banks of questions to be assigned to students. Then, we build training data by determining the value of each question based on Bloom's Taxonomy, item characters/types, and other parameters. Then, with utilizing K-Means, several cluster centers are obtained to represent the uniformity of the questions in the cluster members. By using several heuristics criteria defined previously, several sets or packages of questions that have the same characteristics and difficulty levels are obtained. From the experiments conducted, the analysis with descriptive (i.e., mean, standard deviation, and data visualization) and inference (i.e., ANOVA) statistics of results are presented showing that questions of each sets have the same characteristics to ensure the fairness of examinations. Moreover, by using this system, the contents of the questions in the generated set do not need to be the same, the package of questions can be generated automatically quickly, and the level of the difficulties can be measured and guaranteed.

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The rapid development of technology currently supports all aspects of life, one of which is the office world. The role of technology in the office world which is formed within the scope of office automation accelerates coordination and management of work so as to support the organization or company in achieving its vision and mission. One of the functions of office automation is to support office work, especially in preventing work plagiarism both in terms of documents consisting of text and image elements. This review starts from the definition of plagiarism, the application of plagiarism, research objectives, methods, results and discussion. The purpose of this review is to show the function of the plagiarism detection application in the form of an image as a supporting facility for office automation regarding the importance of detecting plagiarism, plagiarism violations in the office world, how it works and its function in office automation. This study shows that the use of image plagiarism detection applications is very important as a supporting facility for office automation to maintain the quality and image of the organization or company as well as to manage work in an orderly and accountable manner.