Algoritma Genetika Untuk Optimasi Fuzzy Time Series Dalam Memprediksi Kepadatan Lalu Lintas di Jalan Tol

Andhi Surya Wicaksana (Fakultas Ilmu Komputer, Universitas Brawijaya)
Budi Darma Setiawan (Fakultas Ilmu Komputer, Universitas Brawijaya)
Bayu Rahayudi (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 3 (2018): Maret 2018

Fixed and improved traffic facilities continue to be done continuously, but the timing of uncompleted fixes that really only add to the existing traffic congestion will have an impact on the convenience and security of traffic users. Research has been done a lot to predict traffic density but not much focused on traffic on the highway. With fuzzy time series method optimized with Genetic Algorithm method, the writer wants to help solve the problem to predict traffic density on the highway, hopefully the result of research can help as a reference for improvement and improvement of facility in traffic do not increase congestion. Based on the results of top-level testing of predicted results using the Average Forecasting Error Rate (AFER) method, the result of the error rate of 16.66% is included in both qualification and successful.