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All Journal Jurnal Riset Informatika
Sukria Novriana Sari
STMIK Royal Kisaran
Computer Science & IT

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AUTOIMMUNE DISEASE DETECTION WITH DEMPSTER SHAFER AT TANJUNGBALAI GENERAL HOSPITAL Sukria Novriana Sari; Rizky Fauziah; Tika Christy
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2457.992 KB) | DOI: 10.34288/jri.v4i2.337

Abstract

Autoimmune diseases are diseases that attack the human immune system. Autoimmunity is a disorder of the immune system due to the failure of the body's defenses to stabilize conditions so that the immune system attacks a healthy body which is considered a foreign object that must be destroyed. Helping the public in the early detection of autoimmune diseases by using an expert system that is expected to detect autoimmune diseases early in Tanjungbalai Hospital so that they can provide early information about autoimmune diseases and appropriate and informative subsequent actions to the community. In this study, an expert system was built using the web-based Dempster-Shafer method based on the value of expert trust in the symptoms felt by the patient. There were 7 types of autoimmune diseases studied: ITP, SLE, Type 1 DM, Graves Disease, RA (Rheumatoid Arthritis), Autoimmune Hepatitis, and Hashimoto's Thyroiditis. This study resulted in ITP with an accuracy rate of 98%, SLE with an accuracy rate of 96%, Diabetes Mellitus Type 1 with an accuracy rate of 96%, Graves Disease with an accuracy rate of 93%, RA (Rheumatoid Arthritis) with an accuracy rate of 99%, Autoimmune Hepatitis with a 94% accuracy, and Hashimoto's thyroiditis with 99% accuracy.
AUTOIMMUNE DISEASE DETECTION WITH DEMPSTER SHAFER AT TANJUNGBALAI GENERAL HOSPITAL Sukria Novriana Sari; Rizky Fauziah; Tika Christy
Jurnal Riset Informatika Vol. 4 No. 2 (2022): March 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1033.831 KB) | DOI: 10.34288/jri.v4i2.153

Abstract

Autoimmune diseases are diseases that attack the human immune system. Autoimmunity is a disorder of the immune system due to the failure of the body's defenses to stabilize conditions so that the immune system attacks a healthy body which is considered a foreign object that must be destroyed. Helping the public in the early detection of autoimmune diseases by using an expert system that is expected to detect autoimmune diseases early in Tanjungbalai Hospital so that they can provide early information about autoimmune diseases and appropriate and informative subsequent actions to the community. In this study, an expert system was built using the web-based Dempster-Shafer method based on the value of expert trust in the symptoms felt by the patient. There were 7 types of autoimmune diseases studied: ITP, SLE, Type 1 DM, Graves Disease, RA (Rheumatoid Arthritis), Autoimmune Hepatitis, and Hashimoto's Thyroiditis. This study resulted in ITP with an accuracy rate of 98%, SLE with an accuracy rate of 96%, Diabetes Mellitus Type 1 with an accuracy rate of 96%, Graves Disease with an accuracy rate of 93%, RA (Rheumatoid Arthritis) with an accuracy rate of 99%, Autoimmune Hepatitis with a 94% accuracy, and Hashimoto's thyroiditis with 99% accuracy.
Co-Authors Fauziah, Rizky Purwoko, Agus Tika Christy