Implementation of Forward Chaining for Diagnosis of Dengue Hemorrhagic Fever

Abstract

Insects in the form of mosquitoes are transmitting vectors of several types of diseases that are quite dangerous and need to be watched out for because they can be deadly, such as dengue fever mosquitoes, malaria, elephantiasis and the like. Patients suffering from mosquito-borne diseases must be treated immediately to find out the type of disease they are suffering from and their treatment solutions. The era of digitalization that is growing rapidly, including in the field of medical science, makes the use of information technology to help improve quality services for the community. The analysis used in this research is using the forward chaining method, as a comparison of the overall process of the problems obtained in the investigation and developed using the waterfall paradigm. Forward chaining is optimized because the disease diagnosis process begins by observing the symptoms experienced by a patient and then continues with a tracing process that results in conclusions about the dengue fever suffered. While the waterfall method is used in the development of this expert system because the method can accommodate all stages of the system starting from the analysis of functional and non-functional system requirements, system design, coding, expert system testing and the last stage is expert system maintenance. The data used in this study used data at the Maos Health Center, Cilacap Regency. Testing is carried out using the black box testing method where the expert system is tested on end-users to determine the level of success and usability of the developed system. The questionnaire was given to 76 respondents with the results of the questionnaire: 91.9% indicating the level of user satisfaction, 89.6% indicating the level of effectiveness and 92.2% indicating the level of efficiency of the expert system. The output of this study is the conclusion of the disease suffered by the patient and the solution for handling it.

Expert System for Diagnosing Inflammatory Bowel Disease Using Certainty Factor and Forward Chaining Methods

“…The forward chain of this method uses a set of condition and action rules [27]. The data used is later matched to determine which rules will be executed, and the process is repeated continuously until a conclusion is found from the problem being solved [28]. The forward chaining method enters into a multiple inference group that can search from a problem to a solution to that problem [29].…”

Fuzzy expert system design for detecting stunting

“…The benefit of this research is to detect early babies/toddlers who fall into the stunting category by identifying the symptoms experienced by the babies/toddlers and observing them over a certain period of time using an expert system that implements the Mamdani fuzzy method. The difference between this research and research that has been carried out by [23]- [27] is that the method used in this research is a Mamdani fuzzy method which clarifies a problem of uncertainty, inaccuracy and noisy as well as later, the symptoms in the expert system developed will be dynamic in nature and can be added or reduced, adjusted to real conditions in the field [28], [29]. The next update is that the expert system developed can later be used online so that the identification process can be carried out independently without being limited by space and time.…”