TY - JOUR AU - Yasinta Fitriana AU - Nur Hasan AU - Rizky Tarmino AU - Semi Giyai PY - 2022/12/15 Y2 - 2025/04/03 TI - Covid-19 Prognosis Expert System using Forward Chaining Algorithm JF - Jurnal Bumigora Information Technology (BITe) JA - BITe VL - 4 IS - 2 SE - Articles DO - https://doi.org/10.30812/bite.v4i2.2399 UR - https://journal.universitasbumigora.ac.id/index.php/bite/article/view/2399 AB - Coronavirus disease 2019 (COVID-19), which is a global pandemic, has resulted in trillions of losses for Indonesia. Even though the right treatment for COVID-19 can help improve the quality of life again, reduce health and economic problems for the community and the country. Handling/clinical management of the prognosis of a disease can assist doctors, medical teams and researchers in finding patterns of progression of a disease, allocating resources and helping patients and their families to understand more about the patient's condition. Prognosis is a prediction about the development of a disease will improve or vice versa based on the history, diagnosis and clinical management that the patient has gone through. This study builds a COVID-19 prognosis tool and its level of accuracy with intelligent technology based on artificial intelligence, namely an expert system using a forward chaining algorithm. Through the stages of knowledge representation, process modeling, system design, coding and system testing. The result is that the accuracy of the COVID-19 prognosis expert system is 80%, which means that the prognosis expert system with the forward chaining algorithm is effective as a learning tool for health or medical students in studying the prognosis/management of confirmed COVID-19 patients based on available data. ER -