Penerapan Algoritma K-Means Untuk Klasterisasi Balita Rentan Stunting dan Wasting Berdasarkan Indikator Antropometri

Rizky Khairun’nisa; Benni Purnama; Sharipuddin Sharipuddin

doi:10.61132/prosemnasproit.v2i2.155

Authors

Rizky Khairun’nisa Universitas Dinamika Bangsa
Benni Purnama Universitas Dinamika Bangsa
Sharipuddin Sharipuddin Universitas Dinamika Bangsa

DOI:

https://doi.org/10.61132/prosemnasproit.v2i2.155

Keywords:

K-Means, Klasterisasi, Stunting, Wasting, Antropometri

Abstract

Stunting and wasting are nutritional problems in toddlers that remain a double burden of malnutrition in Indonesia and have an impact on the quality of health and future human resource development. Monitoring the nutritional status of toddlers is generally carried out using anthropometric indicators, but the use of this data is still limited to descriptive analysis. This study aims to apply the K-Means algorithm in clustering infants vulnerable to stunting and wasting based on anthropometric indicators, so that groups of infants with different levels of nutritional vulnerability can be identified. The dataset used consists of infant data with variables of gender, age (months), height (cm), and weight (kg). The research stages included data preprocessing, encoding categorical variables, data normalization, determining the optimal number of clusters using the Elbow and Silhouette Score methods, and analyzing the characteristics of each cluster. The evaluation results showed that the optimal number of clusters was four. Each cluster has different anthropometric characteristics and distributions of stunting and wasting status, ranging from groups with relatively normal nutritional conditions, groups with a tendency toward overnutrition, to groups that are vulnerable to acute and chronic malnutrition. These clustering results provide a more comprehensive and segmented mapping of toddlers, which can be used as a basis for formulating more targeted and data-driven nutrition policies and interventions.

References

Ahdika, A., Kartikasari, M. D., Dini, S. K., & Ramadhani, I. (2021). Diversification of Agricultural Areas in Indonesia using Dynamic Copula Modeling and K-Means Clustering. Sains Malaysiana, 50(9), 2791–2817. https://doi.org/10.17576/jsm-2021-5009-24

Aisyah, H. F. (2021). Gambaran Pola Asuh Ibu dengan Balita Stunting dan Tidak Stunting di Kelurahan Tengah, Kecamatan Kramat Jati, DKI Jakarta. Perilaku Dan Promosi Kesehatan: Indonesian Journal of Health Promotion and Behavior, 3(2), 71. https://doi.org/10.47034/ppk.v3i2.4158

Ambarwati, R., Rokhmah, N. N., Andini, S., Fatmi, M., Herlina, N., Rikkit, Nurhikmah, W., Wahyuningrum, C., & Nurmala, S. (2025). UPAYA PREVENTIF STUNTING ANAK: KOLABORASI SKRINING ANTROPOMETRI DAN PRILAKU ORANGTUA SEBAGAI GARDA TERDEPAN. BESIRU : Jurnal Pengabdian Masyarakat, 2(11), 1067–1075. https://doi.org/10.62335/besiru.v2i11.1918

Bahar, Muh. A., Galistiani, G. F., Eliyanti, U., & Mohi, A. R. (2024). Gambaran Nilai Utilitas Kesehatan Anak dengan Malnutrisi: Studi pada Kasus Stunting, Wasting, dan Underweight di Indonesia. Jurnal Mandala Pharmacon Indonesia, 10(2), 610–617. https://doi.org/10.35311/jmpi.v10i2.656

Fitri, D. A., Mikawati, Pratiwi, R., Muaningsih, & Suriyani. (2024). Hubungan Inisiasi Menyusui Dini, ASI Eksklusif, dan Pemantauan Tumbuh Kembang dengan Kejadian Stunting dan Wasting: Kajian di Puskesmas Wilayah Kerja Kassi-Kassi, Makassar. Buletin Ilmu Kebidanan Dan Keperawatan, 3(03), 92–100. https://doi.org/10.56741/bikk.v3i03.612

Hendrastuty, N. (2024). Penerapan Data Mining Menggunakan Algoritma K-Means Clustering Dalam Evaluasi Hasil Pembelajaran Siswa. Jurnal Ilmiah Informatika Dan Ilmu Komputer (JIMA-ILKOM), 3(1), 46–56. https://doi.org/10.58602/jima-ilkom.v3i1.26

Ipmawati, J., & Unggara, I. (2024). Analisis Status Gizi Anak Menggunakan Metode Klastering pada Dataset Anthropometri. Bit-Tech, 7(2), 494–504. https://doi.org/10.32877/bt.v7i2.1869

Kementerian Kesehatan. (2022). Katalog Data—Layanan Permintaan Data | Kementerian Kesehatan RI. https://layanandata.kemkes.go.id/katalog-data/ssgi/ketersediaan-data/ssgi-2022

Mediani, H. S., Hendrawati, S., Pahria, T., Mediawati, A. S., & Suryani, M. (2022). Factors Affecting the Knowledge and Motivation of Health Cadres in Stunting Prevention Among Children in Indonesia. Journal of Multidisciplinary Healthcare, Volume 15, 1069–1082. https://doi.org/10.2147/JMDH.S356736

Mikawati, Lusiana, E., Suriyani, S., Muaningsih, M., & Pratiwi, R. (2023). Deteksi Dini Stunting Melalui Pengukuran Antropometri pada Anak Usia Balita. AKM: Aksi Kepada Masyarakat, 4(1), 277–284. https://doi.org/10.36908/akm.v4i1.862

Munawaroh, S., Fajri, M. N., & Ajija, S. R. (2024). THE EFFECTS OF SOCIAL ASSISTANCE PROGRAMS ON STUNTING PREVALENCE RATES IN INDONESIA. Jurnal Administrasi Kesehatan Indonesia, 12(1), 74–85. https://doi.org/10.20473/jaki.v12i1.2024.74-85

Nozomi, I. (2023). Penerapan Data Mining Untuk Peringatan Dini Banjir Menggunakan Metode Klastering K-Means (Studi Kasus Kota Padang). Jurnal Sains Informatika Terapan, 2(2), 39–44. https://doi.org/10.62357/jsit.v2i2.165

Rasyidah, S., Novianti, A., Angkasa, D., Jus’at, I., & Harna. (2022). Praktik Pemberian Makan dan Status Gizi Balita di Masa Pandemi Covid 19. Amerta Nutrition, 6(1SP), 92–98. https://doi.org/10.20473/amnt.v6i1SP.2022.92-98

Ratnasari, R., Wahidin, A. J., & Andika, T. H. (2024). Deteksi Dini Stunting Pada Anak Berdasarkan Indikator Antropometri dengan Menggunakan Algoritma Machine Learning. Jurnal Algoritma, 21(2), 378–387. https://doi.org/10.33364/algoritma/v.21-2.2122

Saptadi, N. T. S., Chyan, P., & Taga, V. P. (2021). Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City. International Journal on Advanced Science, Engineering and Information Technology, 11(4), 1455. https://doi.org/10.18517/ijaseit.11.4.14487

Setiawan, K., & Saputry, Y. Y. A. (2024). Clustering Data Calon Siswa Baru Menggunakan Metode K-Means di Pusat Pengembangan Anak Fajar Baru Cengkareng. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 8(1), 75–83. https://doi.org/10.35870/jtik.v8i1.1426

Wangsa Nata, M. M., & Setiadi, Y. (2023). Determinan Kejadian Wasting Pada Balita di Provinsi Aceh Tahun 2021. Seminar Nasional Official Statistics, 2023(1), 321–330. https://doi.org/10.34123/semnasoffstat.v2023i1.1619

WHO. (2022). WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age. https://www.who.int/tools/child-growth-standards/standards

Yuwanti, Y., Mulyaningrum, F. M., & Susanti, M. M. (2021). FAKTOR – FAKTOR YANG MEMPENGARUHI STUNTING PADA BALITA DI KABUPATEN GROBOGAN. Jurnal Keperawatan Dan Kesehatan Masyarakat Cendekia Utama, 10(1), 74. https://doi.org/10.31596/jcu.v10i1.704