Penerapan fuzzy inference system metode mamdani untuk peningkatan akurasi klasifikasi kendaraan pada Automatic vehicle classification (avc) system
ABTRACT: Classification of
vehicle's type is
critical in determining
the class of
vehicles passing on the
highway. It is
closely related to
the rate payable
on toll transaction
system for the
vehicle. Misclassification often occurs due to the similarity Bus
vehicle body shape and medium size trucks (Truck Box 3/4), therefore it takes
an expert system to determine the classification of vehicles on the Automatic
Vehicle Classification (AVC) System. The concept of fuzzy logic easy to
understand, mathematical concepts behind
fuzzy reasoning is
simple and fuzzy
logic can work
with conventional control system. This research used fuzzy inference
system with Mamdani method to find
solutions to existing
problems. The length
of the vehicle
body flatness and
long wheelbase Axle as variable
input, while the output variable is the class of the vehicle. The test results
in this study achieved the value of accuracy 86.7%.
Keywords: Classification, Automatic Vehicle Classification (AVC)
System, fuzzy inference system, accuracy
Penulis: Nurofiq, Dosen Teknik
Informatika
Kode Jurnal: jptinformatikadd140009
