DESIGN OF IDENTIFICATION OF SINGLE DEPRESSION DISORDERS USING NATURAL LANGUAGE PROCESSING MODEL IN PATIENT COMPLAINTS

Soma Setiawan Ponco Nugroho (Universitas Muhammadiyah Kudus)
Soma Setiawan Ponco Nugroho (Universitas Islam Indonesia)
Muhammad Najamuddin Dwi (Universitas Islam Indonesia)

Indonesian Journal of Business Intelligence (IJUBI)
Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)

Unconsciously mental disorders often begin with mild symptoms such as anxiety and depression. In cases of depression with long periods of time can result in disruption of a person's mindset and suicidal arising. Based on WHO data in 2010 suicide rates due to depression in Indonesia reached 1.6 to 1.8 per 100,000 people. Unfortunately the symptoms of depressive disorders are often difficult to recognize because a series of patient complaints are in the form of medical narratives or unstructured texts written by doctors. So to get a diagnosis is done by extracting symptoms from complaints data in the form of medical narrative texts. In this study, a design for identifying a single depressive disorder will be built using rule-based reasoning and the Natural Language Processing approach to extract symptoms in a medical narrative or patient complaint text.