One infectious disease is an important health problem in almost all countries, including Indonesia is Tuberculosis caused by Mycobacterium Tuberculosis. This research is to find out the mapping of Tuberculosis in Makassar City in 2015-2017. This study uses a descriptive method with secondary data obtained from Balai Besar Kesehatan Paru Masyarakat Makassar (BBKPM). The population was taken that all patients with suspected tuberculosis were recorded at BBKPM and the samples were tuberculosis patients with Phlegm (+) and (-) examinations. The results of this study were formulated in the form of mapping the spread of tuberculosis patients using Quantum-GIS with a total of 5896. It can be concluded that the largest distribution is in Panakkukang District and the smallest in Wajo District

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Plagiarism is the use of data, language and writing without including the original author or source. The place where palgiate practice occurs most often is the academic environment. In the academic world, the most frequently plagiarized thing is scientific work, for example thesis. To minimize the practice of plagiarism, it is not enough to just remind students. Therefore we need a system or application that can help in measuring the level of similarity of student thesis proposals in order to minimize plagiarism practice. In computer science, the Rabin-Karp algorithm can be used in measuring the level of similarity of texts. The Rabin-Karp algorithm is a string matching algorithm that uses a hash function as a comparison between the search string (m) and substrings in text (n). The Rabin-Karp algorithm is a string search algorithm that can work for large data sizes. The test results show that the use of values on k-gram has an effect on the results of the measurement of similarity levels. In addition, it was also found that the use of the value 5 on k-gram was faster in executing than the values 4 and 6.

The relationship between a course and other subjects described in the curriculum does not explain how much the relationship is supposed to influence the success of students' learning path. Also, some courses are not explicitly written as prerequisites to any other course in the curriculum, but still contribute significantly to the success of the subsequent course. One common way to find the correlation between these courses is by using the classical Pearson Test, but this might ignore the detail of the relationship. This can be improved by incorporating the PCA cross-matrix technique with an improved and more-detailed per-grade relation, not just a general view. This means that students who perform excellently in the previous course might also perform very well in a subsequent one. From the obtained results, it can be seen that the incorporation of the PCA cross matrix technique with a detailed description of the correlation's strength between the prerequisite course and the course it is prerequisite to, based on the results of the former, added more details to the classical Pearson test.

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