IMPLEMENTASI METODE TERMS FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF) DAN MAXIMUM MARGINAL RELEVANCE UNTUK MONITORING DISKUSI ONLINE
ABSTRACT: The application of
social media during the process of teaching and learning especially in online
discussion forum is gradually increased. Neverthelles, the spreading of out of
scope discussion that trigger the emergence of negative debates breaks the communication
etic code in online discussion. This push forward the increasing of admins or
instructurs rules in monitoring and controlling the discussion activity during
the forum session.. By applying TF-IDF and Maximum Marginal Relevancy methods a
software apllication is developed to monitor the discussion online activity.
The list of Text Processing Phase including The sentences breakdown, case
folding, tokenizing, filtering and stemming are conducted to extract the
document posting from the instructurs as well as members comments. Then,
TF-IDF, Query Relevance and Similarity values are calculated. By applying
Maximum Marginal Relavancy, the optimal extraction of documen summary is
provided to reduce the sentences redudancy and rangking output. The comment which
value is zero (0) that based on the comparison of summary between document
posting and members comments will be classfied as “Unfeasible” and recommended
to be eliminated. As the result of accuracy, blackbox and UAT testing in one of
lecture topics this application is success in monitoring the activity of online
discussion with compression value 50% and level accuracy is 76,67%. Hence the discussion forum as one of tool in
incerasing the teaching and learning quality can be optimaized accordingly.
KEYWORDS: Cosine Similarity,
Online Discussion, Comments Feasibility, Maximum Marginal Relevance, Text
Processing, TF-IDF
Penulis: Okfalisa S.T., M.Sc
Kode Jurnal: jptindustridd160271
