Penerapan Algoritma Aprioti Pada Riwayat Data Kecelakaan Lalu Lintas

With the increase of vehicle users, traffic accidents tend to happen more often. One of many ways to minimize the occurrence of traffic accidents is to process accident data history using data mining techniques. This technique is utilized in order to gain information regarding the relational pattern of traffic accidents. The data mining technique used is the association rule technique with the Apriori algorithm. One of the stages of analysis that has attracted the eyes of many researches to produce an efficient Apriori algorithm is analyzing the frequency pattern of an association that can be identified with two benchmarks; Support and Confidence. Currently, the determination of the minimum support value will be repeated by the user until it reaches a positive correlation value. This study applies a certain method to determine the minimum support value with the final result of achieving positive correlation on all datas as a reference for the lift ratio value 1 and getting 6 of the most frequent traffic accident pattern