Classification Of Population Data On Status In The Family Based On Last Education And Work Using The Clustering Method (Case Study: Sei Prison Village Office)


  • Fauziah Ningsih STMIK Kaputama
  • Yani Maulita STMIK KAPUTAMA
  • Marto Sihombing STMIK KAPUTAMA



data mining, k-means algorithm, population data


Population data is structured individual or individual data through population registration, civil registration and population census activities. It is important to know population data because in making policies and planning regional or state development, population data is needed to describe the condition of an area. Population data include births, deaths, transfers or migration, population composition, population density and so on. This grouping is done so that population data that is already in the archives will be input into an application that will be designed to make it easier for parties who need data without having to look at the data that is still manual. The problems that exist are such as the increase in the number of residents in a city, village or even a district which is increasing while the population that has been recorded still does not have a job, such as status in the family, namely the head of the family is still there who does not work in terms of recent education can still be considered to get a job that matches the last type of education. From the research process conducted on 20 data, 3 groups were obtained, Cluster 1 contained 16 data, Cluster 2 contained 1 data, and Cluster 3 contained 3 data. And the most group obtained is cluster 1, there is education last high school, has a type of work that has not worked and status in the family of the head of the family.


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How to Cite

Ningsih, F., Maulita, Y., & Sihombing, M. (2023). Classification Of Population Data On Status In The Family Based On Last Education And Work Using The Clustering Method (Case Study: Sei Prison Village Office). Journal of Artificial Intelligence and Engineering Applications (JAIEA), 3(1), 93–101.