Diagnosis Detection of Acute Respirator Infection With Forward Chaining Method

Abstract

Many acute respiratory infections or ARI are caused by viruses that attack the nose, trachea (breathing tube), or the lungs. It can be said that ARI is caused by inflammation that disrupts a person's breathing process. If not treated quickly, ARI can spread to all respiratory systems and prevent the body from getting proper oxygen, moreover it can cause the loss of a person's life. This research aims to diagnose ARI as an early step in practicing artificial intelligence in medicine, designing and apply an expert system that can diagnose ARI. The procedure used in this study uses forward chaining with tracking that begins with input data, and then creates a diagnosis or solution. The expert system used to diagnose acute respiratory inflammation uses the Forward chaining procedure with a data-driven approach, in this approach tracking starts from input data, and then seeks to draw conclusions, so that it can be used. diagnose the type of disease associated with the ARD disease experienced by showing the existing signs.

Diagnose of Mental Illness Using Forward Chaining and Certainty Factor

“…This study uses the Forward Chaining and Certainty Factor as an inference engine. There are two kinds of certainty factors that are used (Alfiah et al, 2019;Pamungkas et al, 2021), the first is the certainty factor which is filled in by the expert along with the rules. The second is the certainty factor given by the user.…”