IMPLEMENTASI SISTEM PAKAR PADA PASIEN PENDERITA TUBERKULOSIS POTENTIAL DROP OUT DI RUMAH SAKIT CUT MEUTIA ACEH UTARA

Authors

  • Eva Darnila Teknik Informatika, Universitas Malikussaleh, Lhoksumawe, Indonesia
  • Mutammimul Ula Sistem Informasi, Universitas Malikussaleh, Lhoksumawe, Indonesia
  • Mauliza Mauliza Sistem Informasi, Universitas Malikussaleh, Lhoksumawe, Indonesia
  • Ermatita Ermatita Teknik Informatika, Universitas Sriwijaya, Palembang, Indonesia
  • Iwan Pahendra Teknik Elektro, Universitas Sriwijaya, Palembang, Indonesia

DOI:

https://doi.org/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

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Published

2018-10-06