Leprosy is an infectious disease and is considered a public health problem because it is a
neglected disease, and for that reason there is a big problem in preventing and combating
it. In the state of Tocantins, the disease is considered hyperendemic according to the
parameters per 100,000 inhabitants, being one of the states with the most new cases in
Brazil. In view of this problem, it is sought through data from the Information Notification
System (Sinan) that performs the collection of notification of diseases and conditions, the
extraction of knowledge about leprosy cases in the state of Tocantins by applying the
process of knowledge discovery known as Knowledge Discover in Database (KDD) and
through data mining using association rules to characterize people affected by the disease
in the state. The methodology used was of the descriptive and exploratory type, in order
to seek to describe the facts and try to explore the data, exploratory data analysis was used
to explore the relevant attributes of the patient’s characteristics, the disease, the space
and the time. In data mining using association rules, he was responsible for associating
these attributes to know the profile of patients who were frequent in the database in order
to characterize them. The results of the research that were found are that the people most
affected by the disease are people who live in urban areas, and the multibacillary forms
are more common in total, with the male population being the most affected by them.
The education of the population was mostly low, and it was also related to the low income
of the people affected. Every year of the study, the number of cases was hyperendemic
according to national and international parameters.
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