Abstract:
Motor vehicle testing is a vehicle testing process as a determinant of the feasibility of a
vehicle operating on the highway. The goal is to minimize the possibility of accidents and
create safety. The UPTD PKB of the Kampar Regency Transportation Service carried out
motor vehicle testing on 4-wheeled vehicles such as goods transporting cars and passenger
cars. The KIR test includes a pre-test and mechanical test with many criteria that must be
tested on each vehicle. This study aims to built an information system for the proper and
unfit classification of motorized vehicles by applied the C4.5 algorithm and implemented it
into an information system. The system design is designed based on UML and websitebased.
This study used 1729 datasets which are then divided into training and testing data
with a ratio of 80%:20%. So that there are 1383 training data and 346 testing data from
the calculation results obtained 27 rules. The application of data mining on the
classification of the feasibility of motorized vehicles used the C4.5 algorithm produced an
accuracy rate of 97,688%, recall 100%, and precision 97,561%.
