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Implementation of Fuzzy Mamdani Method to Classify Public Health Level in North Sumatra Province
Health is one of the most important fields aspects in people’s lives. Public health is influenced by several factors, such as environmental factors and lifestyle. Every year, the government makes a program to improve people’s health and welfare. Therefore, the government needs to obtain information about the classification of public health levels to monitor the progress of the programs that have been carried out. The research created an interface application to classify the level of public health in North Sumatra Province. The research classified the public health level using data from Badan Pusat Statistik (BPS) in 2018. Next, the application was made using the Matlab 2013b GUI. Classification of the level of public health was carried out using the Fuzzy Mamdani method that generated public health classification levels based on the inputted indicators. Then, the level of health classification was divided into four parts: low, lower middle, upper middle, and high. The result shows that for the 2018 data, some cities/ districts are still at low health levels. However, many cities or districts have good health levels. The final result can be used as a reference for the government to analyze which cities/districts should be paid attention to improve their health and welfare.
Implementation of Fuzzy Mamdani Method to Classify Public Health Level in North Sumatra Province
Health is one of the most important fields aspects in people’s lives. Public health is influenced by several factors, such as environmental factors and lifestyle. Every year, the government makes a program to improve people’s health and welfare. Therefore, the government needs to obtain information about the classification of public health levels to monitor the progress of the programs that have been carried out. The research created an interface application to classify the level of public health in North Sumatra Province. The research classified the public health level using data from Badan Pusat Statistik (BPS) in 2018. Next, the application was made using the Matlab 2013b GUI. Classification of the level of public health was carried out using the Fuzzy Mamdani method that generated public health classification levels based on the inputted indicators. Then, the level of health classification was divided into four parts: low, lower middle, upper middle, and high. The result shows that for the 2018 data, some cities/ districts are still at low health levels. However, many cities or districts have good health levels. The final result can be used as a reference for the government to analyze which cities/districts should be paid attention to improve their health and welfare.
Implementation of Fuzzy Mamdani Method to Classify Public Health Level in North Sumatra Province
Sagita Charolina Sihombing (Autor:in) / Agus Dahlia (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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