Analysis of side effects from using influenza drugs using the Naïve Bayes method

Zul Attoriq Farhan Wahyudi (Universitas Islam Negeri Sumatera Utara, Indonesia)
Abdul Halim Hasugian (Universitas Islam Negeri Sumatera Utara, Indonesia)

Science Midwifery
Vol 12 No 3 (2024): August: Health Sciences and related fields

This study uses the Naive Bayes algorithm to analyze the influence of drug composition on the patient's disease history, with the aim of identifying the risk of side effects from various influenza drugs. This method involves calculating prior, likelihood, and posterior probabilities to evaluate the relationship between drug ingredients and specific medical conditions. The results of the analysis show that a probability value close to 1 indicates a high risk of side effects, such as diabetes patients who are more at risk of decongestant side effects compared to other diseases. Data visualization in the form of pie charts illustrates the impact of various drug ingredients on the risk of side effects in different diseases, helping doctors prescribe appropriate drugs and improving treatment safety. This study concludes that understanding patient risk profiles and drug side effects can be optimized using this analysis technique, supporting better decision making in medical practice.