Application of Apriori Algorithm to Find Patterns of Population Mortality Data (Case Study: Disdukcapil Stabat)

Rizka Nova Fitria

doi:10.59934/jaiea.v5i1.1665

Authors

Rizka Nova Fitria STMIK Kaputama

DOI:

https://doi.org/10.59934/jaiea.v5i1.1665

Keywords:

Apriori algorithm, population mortality, Rapidminer

Abstract

The development of information technology provides great opportunities in data utilization, including in government agencies. One of the important data managed by the Population and Civil Registration Office (Disdukcapil) is population mortality data. This data not only serves as an administrative archive, but can also be analyzed to identify important patterns related to the factors causing death. This study aims to apply the Apriori algorithm in identifying association patterns from population death data based on factors such as age, gender, occupation, cause of death, and address at the Disdukcapil Stabat. The method used is data mining with the Apriori algorithm, through the stages of data processing, determining the support, confidence, and lift values until a rule is formed. The results of the study show that 173 association rules were formed, with the best rule having the highest support value of 6% and confidence of 10%. The rule states that if the age of the population is over 56 years with an address in Stabat, then the tendency of gender is male, occupation as an entrepreneur, and sudden death.

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