Prediksi Kerawanan Wilayah Terhadap Tindak Pencurian Sepeda Motor Menggunakan Metode (S)ARIMA Dan CART
Abstract: Motor vehicle theft
is a crime that is most common in Indonesia. Growth of vehicle motorcycle
significant in each year accompanied by the increasing theft of motorcycles in
each year, we need a system that is able to forecast the development and the
theft of the motorcycle.
This research proposes the development of forecasting models
vulnerability criminal offense of theft of motorcycles with ARIMA forecasting
method. This method not only forecast from variable of theft but also
residents, vehicles and unemployment. The study also determined the
classification level of vulnerability to the crime of theft of a motorcycle
using a method based on the Decision Tree CART ARIMA forecasting method.
Forecasting time series data with ARIMA method performed by each of the
variables to produce the best ARIMA forecasting model which varies based on the
data pattern of each of those variables. The results of classification by CART
method to get the value of accuracy of 92% for the city of Yogyakarta and 85%
for DIY. Based on the above, the results of ARIMA forecasting and
classification CART can be used in determining the level of vulnerability to
the crime of theft of motorcycles.
Penulis: Pradita Eko Prasetyo
Utomo
Kode Jurnal: jptinformatikadd170092
