Data Mining on the Performance of Treatment and Harm Reduction Centers in Isfahan Province in the Correction and Prevention of Drug Addiction

Addiction to drugs, besides the physical and mental losses, causes social and economic problems, such as an increase in drug-related crimes like felony, theft, poverty and begging, and the waste of large material capitals of countries. The purpose of this research is to identify and compare the model of factors related to drug addiction in treatment and harm reduction centers and Anonymous Narcotics Association in Isfahan province inorder to correct and prevent drug addiction. The research method is quantitative and descriptive-analytical. The statistical population includes all people referring to treatment and harm reduction centers and Anonymous Narcotics Associations in the second half of 2019. 1593 sample questionnaires were provided to the centers and 1459 questionnaires were analyzed by removing distortions. Propensity to drugs was measured with the addiction readiness scale of Wade and Butcher, α = 0.9. The results showed that the random decision tree algorithm has the highest prediction accuracy, in each data set, the appropriate algorithm should be explored. The algorithms used in this research have a good ability to predict the tendency to use drugs, and by using the effective factors found, the necessary measures can be taken for the purpose of third prevention. Also, by using the rules found, it is possible to predict the tendency of new people who refer to the centers.