Developing a Framework for Identifying the Scenario of Drug Addiction in Bangladesh

Drug addiction is one of the global concerns that is getting worse. Noakhali claims that there are more drug addicts in Bangladesh than there are people. A person with a drug addiction and one without one differ greatly in terms of their social life, personal habits, family life, and state of health. Thus, with appropriate therapeutic issues, actions should be taken to prevent drug addiction. We should investigate the contributing variables to drug addiction as well as potential remedies to lower the prevalence of drug addiction. The subjects of the study are the residents of Bangladesh’s Noakhali. The majority of the drug-addicted population data is gathered from the Bangladeshi division of Chittagong’s Noakhali and Feni. They range in age from 14 to 85 years old, both male and female. We have gathered 1514 pieces of data in total. Six different algorithms—Logistic Regression, Decision Tree, Random Forest, Naive Bayes, Support Vector Machine (SVM), and KNN—have all been used, and the outcomes are contrasted. SVM had the best results out of all the algorithms: accuracy of 94.45%, precision of 99.11%, recall of 100%, F1-score of 99.9%, and ROC score of 99%. So, this paper is effective and efficient for drug addiction analysis, classify and result compare of Bangladesh.