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Analisis Pengobatan Pasien Menggunakan Model Regresi Logistik Biner Krishna Prafidya Romantica, Krishna
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 6 No. 2 (2019): Sains dan Teknologi
Publisher : Institut Teknologi dan Bisnis Kalbis

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Abstract

Researcher used patient data spread across two residential areas, namely sector 1 and sector2. The research data consisted of four explanatory variables, namely: the age of the patient, the class ofpatients found in the hospital, the patient’s area of residence, and the findings of the disease suffered by the patient. Class, sector, and disease variables are variables categorized into categories 0 and 1. The researcher considers the dummy variables discussed in the explanatory variable variables. Category 0 indicates that the sample does not meet the criteria in the category. Choosing, category 1 shows that the sample meets the criteria in the category. Next, the researcher will estimate the explanatory parameter variables and dummy variables, then do the partial test to get the parameter significance and model it using the Binary Logistic Regression Model. With the Logistic Regression Model, researcher will calculate the consideration of the patient’s recovery. This probability is used as