@thesis{thesis,
		author={Kusuma  Dine Tiara and Mandana  Rizal Adi and Sudirman  M. Yoga Distra},
		title ={Pengembangan Sistem Jurnal dan Penggunaan Text Mining Cosine Similarity dan SVM untuk Penilaian Plagiarism pada Judul dan Abstrak},
		year={2018},
		url={http://156.67.221.169/4530/},
		abstract={Early analysis of journal plagiarism is needed by the editorial team and
partners to evaluate the authenticity of the proposed journal, assessment of
plagiarism is needed to maintain the quality of journal publications. Therefore,
a plagiarism analysis feature is needed in journal management applications,
so it will help in providing information about the journal's authenticity. In this
study SDLC Waterfall is used by applying the Text Mining Cosine Similarity
method and SVM in assessing the level of similarity of a proposed journal with
existing journal data. Application design uses UML and blackbox testing is
conducted to determine the success of applications and evaluation methods
to determine the accuracy of document similarity classification. The results of
plagiarism testing on the electronic journal portal STT-PLN on 30 published
journal journal data with 1836 training data using the Text Mining Cosine
Similarity method and SVM can identify early plagiarism in journals with 100%
precision and 100% recall with susceptible results plagiarism values 5,52% -
29,03%, but if the amount of training data big then takes a long time. With the
early analysis of plagiarism can improve the quality of journal publications}
		}