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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Bagus Ahmad Noverendi
Universitas Bina Insan, Lubuklinggau
Computer Science & IT Decision Sciences, Operations Research & Management

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Implementasi Sistem Pakar Diagnosis Penyakit Pada Ibu Hamil Menggunakan Metode Naïve Bayes Ahmad Sobri; Satrianansyah Satrianansyah; Bagus Ahmad Noverendi
Journal of Information System Research (JOSH) Vol 4 No 4 (2023): Juli 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i4.3836

Abstract

Pregnant women need special attention to maintain their health and that of the fetus they are carrying. To support this process, an expert system has been developed that is capable of diagnosing diseases in pregnant women. The Naïve Bayes method is one of the approaches used in this expert system to classify diseases based on the symptoms experienced by pregnant women. The purpose of this research is to implement an expert system based on the Naïve Bayes method to support the diagnosis of diseases in pregnant women. The Naïve Bayes method was chosen because of its ability to deal with classification problems with incomplete or unbalanced data. After the Naïve Bayes model is a solution, testing and evaluation is carried out using test data. The accuracy of the expert system is measured by comparing the diagnosis given by the system with the actual diagnosis. The results showed that the expert system with the Naïve Bayes method was able to provide an accurate diagnosis for pregnant women. This proves the effectiveness of the Naïve Bayes method in supporting the diagnosis process in pregnant women.
Co-Authors Ahmad Sobri Satrianansyah Satrianansyah