Optimasi Pemodelan Regresi Linier Berganda Pada Prediksi Jumlah Kecelakaan Sepeda Motor Dengan Algoritme Genetika - Sema Yuni Fraticasari; Dian Eka Ratnawati; Randy Cahya Wihandika (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
Traffic accidents are increasing from year to year according to the Badan Pusat Stastistika record from 1992 to 2003. According to the World Health Organization (WHO), it noted that nearly 3,400 people per day died due to traffic accidents. Surabaya is one of the metropolitan cities in Indonesia. Population growth is quite fast because the city of Surabaya is also the capital of East Java province. The system predicts the area of ​​frequent traffic accidents based on the parameters used such as the length of the road, the width of the volume body, the velocity, the number of lanes, the number of directions, the boundary / median, the plot access and the shoulder width by using linear regression optimized with the genetic algorithm. The genetic algorithm uses real numbers with 10 of gene chromosome lengths. The crossover method used by the extended intermediate crossover while the mutation uses random mutation, and the selection uses elitism selection. From the results of the experiments conducted to produce population is 125, the best combination of cr and mr is 0,6:0,4 and the best generation is 700. Comparison of error rate by showing a lower error value of 0,5% compared with regression Which results in an error value is 1,5%.