@thesis{thesis,
		author={Bardadi  Ali and Jambak  Muhammad Ihsan and MAHARANI  ANINDYA DEWI},
		title ={KLASTERISASI ABSTRAK SKRIPSI MAHASISWA FAKULTAS ILMU KOMPUTER},
		year={2023},
		url={http://repository.unsri.ac.id/104894/},
		abstract={Currently, it is often found that the writing of thesis abstracts seems haphazard. The Faculty of Computer Science, Sriwijaya University, as an institution that organizes undergraduate education, is fully committed to improve the quality of its students by using thesis as a benchmark of students' abilities in their field of study. To maintain its consistency in the development of study programs, the Faculty of Computer Science, Sriwijaya University, requires the right strategy in the implementation of the study programs. This research applies the utilization of data mining science in processing the thesis data of computer science students to group thesis abstracts based on study programs (Information Systems, Informatics Engineering, and Computer Systems). Data processing, using the RapidMiner application, produces 3 thesis clusters based on the similarity between thesis abstracts. From the cluster analysis that had been conducted, it was found that each program has different characteristics of thesis abstracts in the form of words that often appear in abstracts. The findings of this study can serve as a guide for students who are currently preparing their thesis and as feedback for their thesis advisors to provide guidance in creating a good abstract.}
		}