Owen Hartanto
Sistem Informasi, Fakultas Saint dan Teknologi, Universitas Prima Indonesia, Kota Medan, 20118, Indonesia

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Comparative Analysis of Fuzzy C-Means and K-Medoids Algorithms in Addressing the Level of Stunting Distribution in Deli Serdang Regency Tajrin Tajrin; Owen Hartanto; Justin Frederick
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9194

Abstract

The health and development of children under five are crucial indicators of a country's social and economic success. Malnutrition in toddlers is a major challenge affecting the quality of human resources. The prevalence of stunting in Indonesia remains high, although there has been a decline. Data from the Indonesian Nutritional Status Survey (SSGI) conducted by the Health Development Policy Agency (BKPK) of the Ministry of Health of the Republic of Indonesia (Kemenkes RI) officially announced that the prevalence of stunting in Indonesia for 2024 will be 19.8%. Deli Serdang Regency in early June 2024 was 45.8% to 23.2% in November 2024 there was a decrease in stunting by 22.6%, although there was a decrease in stunting rates but the figure was still quite high from the national prevalence rate of 19.8%, based on this study the results of the comparison of the Fuzzy C-Mean and K-Medoid algorithms with a total of 394 data produced a lower stunting rate equation in cluster 1 with a different number of regions, and cluster 2 higher stunting rates with a different number of regions, the FCM algorithm produced 51 lower children in cluster 1 in cluster 2 totaling 343 more lower children and higher prevalence and variation between clusters of 71.02% while the K-Medoid algorithm produced 127 short children in cluster 1 in cluster 2 the number of children was very large 899 shorter children and a lower prevalence of 0.417%.