Peramalan Jumlah Kasus Tuberkulosis di Rumah Sakit Umum Haji Medan dengan Metode Support Vector Regression-Particle Swarm Optimization
Abstract
Tuberculosis is an infectious disease that is the leading cause of poor health and one of the major causes of death around the world, in 2021 north Sumatra ran sixth as the province with the highest Tuberculosis rate after Provinsi Jawa Barat, Jawa Tengah, Jawa timur, DKI Jakarta, and Banten. This may result from an unhealthy environment, an increase in nutrition events, the appearance of HIV/AIDS. Hence, this study aims to create a forecast model by the method of regression support (SVR) with an optimist Particle Swarm Optimazion (PSO). The initial stage of the study involves analyzing the data of those with tuberculosis that begins by calculating the correlation between data with the underlying factors. Then do the preprocessing to initial data value, selecting the number of features and normalization of data. After the analysis stage, regression calculations are made to compare the value of browsing and actual value using the Support Vector Regression (SVR) method of Support Vector Regression (SVR) with the Particle Swarm Optimization (PSO) so that a good fortune-giving result is obtained. The results of this study were obtained from an analysis with a value of MAPE = 35.85.
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References
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Copyright (c) 2024 Sumawiyah Hsb, Ismail Husein, Rina Widyasari
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