A suggestion system can help the user create a clear grasp of their needs and make wellinformed recommendations based on a wealth of complex information. One of the most serious medical mistakes that could endanger patients' lives is drug errors. To help consumers make more sensible and costeffective healthcare choices, these issues highlight the need for recommendation frameworks within the medical sector. By taking into account these issues, this paper aims to create a drug suggestion system that will assist users in identifying the best medications for a given wellness based on the feedback from users who have used different drugs for a variety of specific illnesses. Employing an Improved Sentiment Analysis with Support Vector Machines, the study's goal was achieved. (ISA-SVM). When the proposed approach's findings are contrasted with those of related previous work, it is discovered to produce superior outcomes to those of the extant systems.