MODELING CHRONIC FILARIASIS CASES IN WEST JAVA USING A MULTIVARIATE ADAPTIVE APPROACH REGRESSION SPLINES

  • Ardi Kurniawan Department of Statistics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0002-2840-2154
  • Mochammad Firmansyah Department of Statistics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Toha Saifudin Department of Statistics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
Keywords: Modeling, Chronic Number of Filariasis, Multivariate Adaptive Regression Spline

Abstract

One of the most crippling infectious diseases in the world is filariasis. Indonesia is a unitary country with 34 provinces, where West Java is one of the 5 provinces with the most filariasis sufferers in Indonesia as of 2021. Reinfection occurs in places that have implemented POMP. Therefore, monitoring operations must be carried out to track the emergence of new cases and risk factors for transmission. The aim of this research focuses on describing and modeling the number of chronic filariasis in West Java, as well as interpreting the best model results obtained. The method used is a method with a nonparametric regression approach, namely Multivariate Adaptive Regression Spline. The results of the research show that the best model obtained is a combination of 15 base functions, maximum interaction 2, and minimum observation between knots 1. From this model, the predictor variable that has the most influence on the response variable in order based on the level of variable importance is the Percentage of Population Access to Facilities Decent Sanitation, Percentage of Households with Clean and Healthy Behavior (PHBS), Sex Ratio, and Percentage of Poor Population. The interpretation of the best model is that the variable Percentage of Population Access to Adequate Sanitation Facilities above 6,650% will contribute to a reduction in the number of chronic filariasis; the Sex Ratio variable below 103,300 will contribute in the form of a reduction in the number of chronic filariasis. it can be seen that the predictor variable that has the most influence on the response variable is the variable Percentage of Population Access to Proper Sanitation Facilities  with an importance level of 100%.

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Published
2024-05-25
How to Cite
[1]
A. Kurniawan, M. Firmansyah, and T. Saifudin, “MODELING CHRONIC FILARIASIS CASES IN WEST JAVA USING A MULTIVARIATE ADAPTIVE APPROACH REGRESSION SPLINES”, BAREKENG: J. Math. & App., vol. 18, no. 2, pp. 1249-1260, May 2024.