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All Journal Computing and Information System Journal
Rayhan Ibrahim
Fakultas Teknik, Universitas Muhammadiyah Jember
Computer Science & IT

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EARLY DETECTION OF DIABETES MELLITUS TYPE 1, TYPE 2, AND GESTATIONAL DIABETES MELLITUS (GDM) USING WEBSITE-BASED CERTAINTY FACTOR Rayhan Ibrahim; Guruh Wijaya; Dudi Irawan
Computing and Information System Journal Vol. 2 No. 1 (2026): Inovasi Teknologi Cerdas Berbasis AI, IoT, dan Data Mining di Era Digital
Publisher : IndoCompt Publisher

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Abstract

The development of information technology plays an important role in supporting healthcare services, particularly in assisting the early detection of diseases. One chronic disease that requires early detection is Diabetes Mellitus, which consists of Type 1 Diabetes Mellitus, Type 2 Diabetes Mellitus, and Gestational Diabetes Mellitus (GDM). These three types of diabetes have similar early symptoms, making them difficult to recognize by the general public. Therefore, this study aims to design and develop a web based expert system to detect Type 1 Diabetes Mellitus, Type 2 Diabetes Mellitus, and Gestational Diabetes Mellitus (GDM) using the Certainty Factor method. This method is used to calculate the level of diagnostic confidence based on symptoms selected by users, referring to confidence weights provided by medical experts. The problem-solving process is carried out through Certainty Factor calculations using a weighted average approach to generate the percentage of diagnostic confidence. Based on testing and validation results through manual calculations and expert evaluation, the developed system achieved an accuracy rate of 87.10%. The results indicate that this expert system can be used as a supporting tool for the early detection of Diabetes Mellitus prior to further medical examination.
Co-Authors Irawan, Dudi Wijaya, Guruh