Stunting is a chronic nutritional problem that occurs in toddlers, defined based on height for age (TB/U) which is less than two negative standard deviations or a toddler's height is shorter than it should be. Stunting is a chronic nutritional problem in toddlers, characterized by a shorter height than the height of children his age. Bulungan Regency is one of 160 urban regencies in Indonesia that is intervened to focus on reducing stunting. Based on these problems, this study aims to determine the cluster of stunting vulnerabilities in Bulungan Regency. The method used is Fuzzy C-Means (FCM). The results of this study are that the area in cluster 1 has a high level of vulnerability because it has the lowest level of adequacy of posyandu (active) and high incidence of LBW in infants, cluster 2 has a moderate level of vulnerability because it has an adequate level of puskesmas, adequacy of posyandu (active), the adequacy of doctors, the adequacy of nutritionists, the adequacy of midwives, the percentage of moderate LBW, and cluster 3 have a low level of vulnerability because they have a low average percentage of LBW and a high level of adequacy of posyandu (active) in the area.
Hingga saat ini, penyakit Demam Berdarah Dengue (DBD) masih saja menjadi salah satu epidemi penyakit tertinggi di Indonesia. Permasalahan ini terjadi pula di wilayah Kalimantan Utara. Dengan kondisi wilayah Kalimantan Utara yang berupa gugusan pulau, sulit bagi para tenaga kesehatan untuk mengakses daerah-daerah yang rawan epidemi DBD tersebut. Hal itu ditambah lagi dengan belum adanya peta prediksi penyebaran DBD di wilayah Kalimantan Utara. Oleh karena itu, perlu kiranya dilakukan sebuah penelitian yang bertujuan untuk membangun peta penyebaran penyakit ini di wilayah Kalimantan Utara dengan mempertimbangkan berbagai macam parameter penyebaran di antaranya jumlah populasi, tingkat infeksi, dan laju kesembuhan. Metode yang digunakan pada penelitian ini adalah metode Fuzzy C-Means. Tahapan metode penelitian yang akan dilakukan meliputi mengumpulkan sampel data penderita DBD di wilayah Kalimantan Utara, perhitungan secara matematis, implementasi program GUI Matlab, simulasi program. Sumber data yang digunakan adalah data sekunderdari Dinas Kesehatan Kalimantan Utara Tahun 2018 dan Badan Pusat Statistik (BPS). Hasil yang diperoleh cluster 1 dengan indikator tinggi wilayah Tarakan, cluster 2 dengan indikator sedang wilayah Malinau dan Nunukan, serta cluster 3 dengan indikator rendah wilayah Bulungan dan Tana Tidung.
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