| dc.description.abstract | Fuzzy logic begins with the concept of fuzzy set. A fuzzy set describing the
relationship between the quantity given x and the membership function (p), which
ranges between 0 and l, fuzzy provides a simple way to arrive at a definite conclusion
based on the input information is vague, ambiguous, imprecise, noisy,
or missing- Tsukamoto fuzzy inference modeling provides better performance and
more consistent and mathematically in the handling of uncertainty due to input
linguistic variable process provides better output results with the results output using
mathematical models other classics. In this research of three input variables that
affect road conditions in general, and as many as four years of data, from the data
generated 27 rules to make a prediction of road conditions niali future dating. From
the results obtained prediction that the results are very accurate which reached 98%
accuracy rate, from these results it can be concluded that the model is suitable
Tsukamoto fuzzy inference in terms of prediction and prediction for cases in some
road in North Sumatera- | en_US |
