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All Journal International Journal of Health, Engineering and Technology
Rika Handayani4
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Dentistry Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Classification of Infertility Risk in Female Patients Based on Medical Record Data Using Naive Bayes Algorithm fahruzisirait; Halimah Tusakdiyah Harahap; Nadya Fitriani; Rika Handayani4; Baginda Restu Al Ghazali
International Journal of Health Engineering and Technology Vol. 4 No. 3 (2025): IJHET SEPTEMBER 2025
Publisher : CV. AFDIFAL MAJU BERKAH

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Abstract

Infertility is a reproductive health problem that has a significant impact globally, especially in developing countries such as Indonesia. This study aims to classify the risk of infertility in female patients at Rantauprapat Regional Hospital by utilizing the Naive Bayes algorithm based on electronic medical record data. The data used consisted of 500 medical records of female patients of childbearing age during the period 2019–2022, which had been processed and divided into training data (70%) and testing data (30%). The analysis and modeling process was carried out using the RapidMiner application without requiring programming skills. The results showed that the Naive Bayes model was able to classify the risk of infertility with an accuracy level of 86.7%, precision of 91.0%, recall of 93.2%, and F1-score of 92.1
Co-Authors Baginda Restu Al Ghazali fahruzisirait Halimah Tusakdiyah Harahap Nadya Fitriani