Sistem Pakar Menggunakan Teorema Bayes Dalam Rekomendasi Penentuan Jenis Anestesi Pada Pasien

Abstract

This study discusses the problem, namely the process of determining the type of anesthesia for patients before carrying out surgery. In determining the appropriate type of anesthesia based on the conditions experienced by the patient, generally anesthesiologists or anesthesiologists still use the common method, namely by conducting interviews related to the symptoms experienced by patients before anesthesia is carried out on patients who will be operated on. Then the anesthesiologist will write down the results of the interview in the form of a written report and will adjust the results of the interview related to the symptoms experienced with the existing anesthesia guidelines. And this will certainly take more time in adjusting the results of the patient's symptoms to the type of anesthesia that will be given. Along with the rapid development of technology, determining the type of anesthesia that will be given to the patient before it is carried out can be overcome by building an information system that is able to adopt the process and way of thinking of humans, namely Artificial Intelligence or artificial intelligence which is often called the Expert System. In this case, a smart application in determining the type of anesthesia in android-based patients is designed using the Bayes Theorem calculation method, and it is possible for an anesthesiologist and anesthesiologist to administer anesthesia to a patient before a patient steps into the operation stage. Thus, it can also cause work productivity to increase and the time used to complete the work is getting shorter

Algoritma Forward Chaining dan Teorema Bayes Dalam Sistem Pakar Screening Parafilia

“…Selanjutnya, persamaan tersebut akan menghasilkan nilai Bayesₙ yang kemudian dijumlahkan untuk mendapatkan nilai hasil bayes seperti pada persamaan berikut [11]:…”