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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Riki Antoni
Universitas Pamulang
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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SISTEM PAKAR DETEKSI PENYAKIT DIABETES MELLITUS DENGAN MENGGUNAKAN PENDEKATAN NAÏVE BAYESIAN BERBASIS WEB (Studi Kasus : PUSKESMAS Kelurahan Grogol 3) Riki Antoni
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 01 (2023): OKTAL : Jurnal Ilmu Komputer dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Diabetes mellitus (DM) is a chronic disease that will suffer for a lifetime and has a major impact on human quality of life and requires substantial medical expenses. Diabetes mellitus can trigger various complications of dangerous diseases and require long-term treatment. However, there are still many people who do not have high awareness of the dangers of this disease and also do not have basic knowledge about this disease and experience limited time so they rarely consult a doctor. Currently, there is no website that can replace the role of doctors in diagnosing diabetes mellitus which can provide convenience to the public in diagnosing diabetes mellitus. Building an expert system capable of diagnosing diabetes mellitus will greatly assist patients in diagnosing diabetes mellitus earlier. The Naïve Bayes method used in the Diabetes Mellitus Detection Expert System can classify diabetes mellitus. Using the MySQL database is capable of being a good dataset storage medium and training data in the Diabetes Mellitus Disease Detection Expert System.
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