Comparison of the Effects Stemmer Porter and Nazief-Adriani on the Performance of Winnowing Algorithms for Measuring Plagiarism
Alam Rahmatulloh, Neng Ika Kurniati, Irfan Darmawan, Adi Zaenal Asyikin, Deden Witarsyah J
Journal of Digital Information Management, Vol. 18, No. 2, 2020.
DOI: https://doi.org/10.6025/jdim/2020/18/2/49-56
Link: 
Abstract:
Current technological developments change physical paper patterns into digital, which has a very high impact. Positive impact because paper waste is reduced, on the other hand, the rampant copying of digital data raises the amount of plagiarism that is increasing. At present, there are many efforts made by experts to overcome the problem of plagiarism, one of which is by utilizing the winnowing algorithm as a tool to detect plagiarism data. In its development, many optimizing winnowing algorithms used stemming techniques. The most widely used stemmer algorithms include stemmer porter and nazief-adriani. However, there has not been a discussion on the comparison of the effect of performance using stemmer on the winnowing algorithm in measuring the value of plagiarism. So it is necessary to do research on the effect of stemmer algorithms on winnowing algorithms so that the results of plagiarism detection are more optimal. The results of this study indicate that the effect of nazief-adriani stemmer on the winnowing algorithm is superior to the stemmer porter, only decreasing the detection performance of the 0.28% similarity value while the porter stemmer is superior in increasing the processing time to 69% faster.