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Grouping the health level of toddlers using Fuzzy Subtractive Clustering method in Makassar City.

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Clustering-fuzzy-subtractive

Grouping the health level of toddlers using Fuzzy Subtractive Clustering method in Makassar City.

Research purposes : The goal to be achieved is to find out the grouping of toddlers's health levels for each urban village in Makassar City.

Scope of problem :

  • Only focused on determining nutritional status in children aged less than 5 years or 0-60 months.
  • The data used is a dataset of children under five in each urban village that comes from the Makassar City Health Office in 2018.
  • The parameters used are the toddler mortality rate, the percentage of toddler undernourished, the percentage of toddler skinny, the percentage of toddler short, the percentage of low birth weight (LBW), the percentage of toddler suffering from pneumonia, and the percentage of toddler suffering from diarrhea.
  • The programming application that will be used is Matlab.

Conclussion : The use of the fuzzy subtractive clustering algorithm using r = 0.55 on the toddler dataset in each urban village originating from the Makassar City Health Office in 2018 both with work without a library or using a library in Matlab gives the same cluster results, namely 5 clusters. By knowing clusters in each urban village that have the same problem, the government can use it as a policy material to be able to improve health services in each urban village based on the problems faced, so as to reduce mortality and disease rates and improve the nutritional status of children under five.

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Grouping the health level of toddlers using Fuzzy Subtractive Clustering method in Makassar City.

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