@thesis{thesis,
		author={Abdurrasyid  Abdurrasyid and Arianto  Rakhmat and Wicaksono  Bayu},
		title ={SMART AND INTEGRATED LABORATORY REPORT ASSESSMENT SYSTEM (SILARAS) DENGAN METODE PROBABILISTIC LATENT SEMANTIC ANALYSIS},
		year={2018},
		url={http://156.67.221.169/4493/},
		abstract={This study discusses the making of SILARAS application (Smart and Integrated
Laboratory Report Assessment System) which purposed to correct a document
report on Algorithm & Programming 2 courses by using PLSA (Probabilistic
Latent Semantic Analysis) text mining calculation method. PLSA is one of the
methods in text mining used to summarize a text document purposed at obtaining
a topic discussion group contained in the document or can be called as topic
modeling by calculating the probability value of the word on the topic, the
probability of the topic on the document, and the probability of the word and
document on topic. Before the calculation of PLSA is done first pre-processing
step to reduce the number of matrix dimensions to be easier when used as input
parameters into the PLSA method that includes tokenizing, filtering, and
stemming. It then calculates the number of occurrences of word / term queries in
the document being tested and used as input parameters for the calculation of
the PLSA method. Performance testing results of PLSA using accuracy method
by calculating how percentage probability topics in documents successfully
calculated and yield accuracy of 74.99%. Based on these percentages can be
concluded that the PLSA method can be an option to summarize the text of the
document so that it can assist the laboratory assistant in correcting student
reports.}
		}