Analysis of DHF Patients Based on Laboratory Examination Results with Nonparametric Approach

Tiani Wahyu Utami; M. Al Haris; Nadia Khoirunnafisa Salma

doi:10.31764/jtam.v10i1.33609

Analysis of DHF Patients Based on Laboratory Examination Results with Nonparametric Approach

Tiani Wahyu Utami, M. Al Haris, Nadia Khoirunnafisa Salma

Abstract

The dengue virus, which is spread by the Aedes aegypti mosquito, is the cause of Dengue Hemorrhagic Fever (DHF). In the city of Semarang, there was a threefold increase in cases of DHF compared to previous years. This type of research is quantitative research because it produces function that describes the relationship to what extent changes in predictor variable are related to changes in response variable to understand the level of association. Modelling the link between response and predictor factors is the aim of this study. Platelet as the response variable and hemoglobin and leukocyte as the predictor variables, so that the obtained model can be used as a prediction, especially regarding the dynamics of platelet changes influenced by hemoglobin and leukocytes. The pattern of the relationship between platelets and the suspected influencing factors does not form specific pattern, so the Nonparametric Spline method is used in this study. The Spline method is chosen for its flexibility; this model tends to independently seek data estimates, the completion of this study using R software. In the Spline method, there are knot points indicating data changes. The selection of optimum knot points is done by choosing the minimum GCV value The secondary data used came from Roemani Muhammadiyah Hospital's 2023 medical records. The data include platelet count, hemoglobin, and leukocyte. Based on the modeling conducted using truncated spline, the optimum knot points on the linier spline are determined to be 3 knot points with a coefficient determination of 83.58%. The coefficient of determination of 83.58% indicating that 83.58% of the variation in response variable can be explained by predictor variables studied in the regression model. This value indicates that predictor variables have a strong ability to explain changes in response variable.

Keywords

Dengue Hemorrhagic Fever; Nonparametric Regression; GCV; Spline Estimator.

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DOI: https://doi.org/10.31764/jtam.v10i1.33609