Implementasi Metode Certainty Factor dan Bayesian dalam Sistem Pakar Diagnosa Inkontinensia Urine Lansia

Abstract

Urinary incontinence is a medical condition commonly experienced by the elderly, requiring prompt and accurate diagnosis for effective treatment. This study aims to develop and compare the performance of two methods in expert systems for diagnosing urinary incontinence in the elderly: Certainty Factor and Bayesian. The developed expert system is web-based and utilizes a symptom dataset collected from the Santa Monika Boro Nursing Home. The findings reveal that the Certainty Factor method excels in diagnostic processing speed, while the Bayesian method offers higher accuracy in diagnostic predictions. This comparison provides valuable insights into selecting appropriate approaches for expert system applications in medical settings.