Abstract:
Understanding the final assignment with multiple pages takes a long time and it’s not
efficient sometimes. This research was made to create automatic summarizing. The data
used is chapter IV of the final assignment of the student Information System who
graduated in 2018.. Process of the text preprocessing is divided into several parts, case
folding, filtering, stemming and tokenizing. After the data passed through the text
preprocessing process, the data will be weighted using Term Frequency-Inverse
Document Frequency (TF-IDF) method. Then the process of grouping can be done by
using k-means clustering method. Testing use compression rate showed 89.06%
information in the document successfully summarized and testing use silhouette coefficient
shows an average value of 0.202920986 with the mean quality of the cluster in the good
category.
Keywords
