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Mauliza, Mauliza
STMIK Budi Darma
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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IMPLEMENTASI SISTEM PAKAR PADA PASIEN PENDERITA TUBERKULOSIS POTENTIAL DROP OUT DI RUMAH SAKIT CUT MEUTIA ACEH UTARA Darnila, Eva; Ula, Mutammimul; Mauliza, Mauliza; Ermatita, Ermatita; Pahendra, Iwan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.968

Abstract

The existence of a technology that identifies and controls patients with potential drop out TB disease which is increasingly rapid will be a top priority, especially for the health team in following up the success of treatment. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis by using a Case Based Reasoning model to see patients with potential Droup Out. For variable names used are pulmonary smear patients (+), new patients, pulmonary smear (-) / ro (+), new patients, extra pulmonary, relapsed patients, re-treatment, default patients, re-treatment patients, failed patients and others -other. The last detection process is taken from the highest value obtained in the diagnosis of all the symptoms that have been witnessed. Based on the results of the application of the Expert System on Potential Drop Out Tuberculosis Patients at Cut Meutia Hospital in North Aceh based on the case code 31 with a detection system for the AFB (+) Lung Patient with its detection symptoms, the patient coughs with phlegm for 2-3 weeks or more. the results of sputum examination, patients who have been treated with TB drugs less than 1 month and TB patients on sputum examination, patients who have been treated with TB drugs less than 1 month, TB patients stop the treatment and TB patients return to the facility health service facilities with the highest case value of 0.6111 of all detection systems that have been tested.Keywords: Expert system,  CBS, TB
TEKNOLOGI SISTEM PAKAR DALAM MENDIAGNOSA BERAT BADAN LAHIR RENDAH MENGGUNAKAN CASE BASED REASONING (CBR) Mauliza, Mauliza; Hamdhana, Defry
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.969

Abstract

Body Weight is one indicator for health of newborns (BBL). The health of newborns is a seriously problem and one indicator for the cause of infant mortality in Indonesia. In this case, we use expert system with case based reasoning (CBR) methods to diagnosis the low birth weight. Our paper aims to knows risks factor which measurement the low birth weight and can develop the hospital system to diagnose the initial symptoms of newborns type. We use age, HB rate, parity distance, number of antenental visits, amount of parity, socio-economy status, mother’s education level, and nutrition status of pregnant while the maternal work history variable is a protection factor.Keywords: Expert System, CBS, low birth weight
Co-Authors Ermatita - Eva Darnila Hamdhana, Defry Mutammimul Ula Pahendra, Iwan