Implementasi Metode Forward Chaining Pada Diagnosa Penyakit Malaria

Malaria is a serious disease caused by the Plasmodium parasite, transmitted through the bite of Anopheles mosquitoes. This disease can cause various symptoms, ranging from fever, headache, and chills to more severe complications such as severe anemia, organ damage, and even death if not treated properly. Therefore, rapid and accurate diagnosis of malaria is crucial for effective treatment and can save lives. This article discusses the implementation of the forward chaining method in a Python-based program for the diagnosis of malaria. Forward chaining is an inference technique in expert systems used to draw conclusions from a series of available facts or data. In this context, the forward chaining method enables the identification of symptoms associated with malaria based on input data provided by the user. By using the forward chaining algorithm, the system automatically processes this data to provide initial diagnosis recommendations and appropriate treatment. This implementation is expected to assist medical personnel in making faster and more accurate decisions, reducing workload, and improving efficiency in handling malaria cases, especially in endemic areas. This article also evaluates the performance of the developed system and discusses challenges and further development prospects in expert system-based diagnostic applications for malaria. The evaluation shows that this system has great potential in supporting medical personnel and speeding up the diagnosis process, which is crucial in managing malaria