Implementasi Sistem Pakar untuk Mendeteksi Virus Covid-19 dengan Perbandingan Metode Naïve Bayes dan Certainty Factor

Abstract

The Covid -19 virus spread in the world, especially in Indonesia, very fast. This epidemic is of concern around the world because it has a quite bad impact in various sectors. With existing technological advances, the Expert System can assist medical personnel in detecting the Covid -19 Virus. The purpose of the author in conducting the study was to detect the Covid-19 virus as easily as possible with symptom data obtained from patients who had consultations. The Naïve Bayes method is a method that uses probability and statistics that can predict a person's chance of being exposed to Covid-19 in the future based on symptoms experienced in the previous period packed with a web-based program. For comparison, the author uses the Certainty Factor Method. Certainty Factor is a method that aims to determine the certainty value which is based on the previous calculation of CF value by manual calculation. The Naïve Bayes method can group the symptoms obtained from the official WHO website which has been given an indicator of the percentage of someone exposed to the Covid-19 Virus based on the symptom data experienced to determine a person exposed to the Covid-19 Virus. While the Certainty Factor method gets the confidence of someone exposed to the symptoms of the Covid-19 virus by using the calculation indicator on the CF value that has been consulted by the user, which can provide a percentage level of confidence that is 86%.Keywords:Expert System, Covid-19, Naive Bayes, Certainty Factor.

Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19

“…The following is a graph of the accuracy of the nave Bayes method of 96%, with 48 test data according to the calculation of the nave Bayes method of testing with expert diagnoses (experts) and 4%, with 2 test data that have different answers from expert diagnoses as in Figure 3. The results of this study indicate that there are differences in the results of the analysis with previous research conducted by [25] by comparing the nave Bayes method and certainty factor in an expert system to detect the COVID-19 virus. The test results from this study obtained a percentage value of 86% confidence level.…”

Rancang Bangunan Sistem Pakar Diagnosa Penyakit Dan Hama Tanaman Bawang Merah Dan Cabai Menggunakan Metode Certainty Factor

“…Selain itu, "Sistem Pakar Diagnosis Penyakit Mata Menggunakan Naive Bayes Classifier" dapat mendiagnosis pendapat ahli dengan akurasi 83%. Sementara itu, metode "koefisien determinasi" untuk menentukan kepastian seseorang terkena gejala virus corona dapat memberikan tingkat kepercayaan sebesar 86% dengan menggunakan metrik yang dihitung berdasarkan nilai CF yang dikonsultasikan oleh pengguna [11]. Sistem pakar diagnosa hama dan penyakit semangka menggunakan metode faktor keamanan dan akurasi 80% [12].…”

Perancangan Diagnosa Covid-19 Menggunakan Metode Case Based Reasoning (CBR) Untuk Mengidentifikasi Tingkatan Gejala Pasien Covid-19

“…Apabila masyarakat hendak mendiagnosa penyakit covid-19, masyarakat harus langsung menjalani tes PCR/SWAB ke fasilitas kesehatan terdekat, tentu saja ini dapat menghabiskan waktu dan uang, jika proses ini dilakukan secara berulang. Sementara itu, untuk melakukan screening awal tidak harus langsung melakukan tes PCR/SWAB, hanya diperlukan beberapa survei untuk mengusulkan apakah orang tersebut harus melakukan tes covid-19 atau tidak [8]. Dengan demikian, ada beberapa tingkatan gejala yang dialami pasien covid-19 yaitu, tanpa gejala, gejala ringan, gejala sedang, dan gejala berat.…”