Analysis of the Number of Children Owned by Nursing Home Residents Using the C4.5 Algorithm

Muhammad Indra; Darmeli Nasution

doi:10.61306/jitcse.v1i3.90

Authors

Muhammad Indra Universitas Pembangunan Panca Budi
Darmeli Nasution Universitas Pembangunan Panca Budi

DOI:

https://doi.org/10.61306/jitcse.v1i3.90

Keywords:

Nursing Home, C4.5 Algorithm, Data Mining

Abstract

Advances in information technology, particularly in data mining and machine learning, offer opportunities to increase the efficiency of nursing home management. This research aims to analyze the pattern of the number of children in nursing homes using the C4.5 algorithm, providing insight for managers to design more effective programs. The data used in this research is secondary data from the UPTD population list for Elderly Social Services for the period January to September 2024. Using RapidMiner software, a decision tree model was built to group the population based on the number of children. The analysis revealed five categories of citizens: no children, one child, two children, three children, and five children. The largest number of residents (285 people) have no children, followed by residents who have one child (63 people), three children (45 people), two children (9 people), and five children (8 people). These findings indicate that residents who do not have children are more likely to choose to live in nursing homes. This study provides a basis for increasing interaction between residents and their families, especially for those who do not have children. Further research with larger samples is needed to explore other factors influencing nursing home residents' decisions.

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