Penerapan Algoritma K-Means dalam Mengelompokkan Balita yang Mengalami Gizi Buruk Menurut Provinsi

Abstract

The purpose of this study was to screen toddlers who were experiencing severe malnutrition according to province. Sources of research data used were obtained from the Ministry of Health of the Republic of Indonesia. The variables used are toddlers who experience malnutrition according to the Province. In this study using Data Mining Techniques using the K-means algorithm. It is expected that the results of this study can provide input to the central government to pay more attention to nutritional intake in infants, so as to increase the growth and development of toddlers in Indonesia. . And the data obtained by high clusters are 15 Provinsi yaitu (Aceh, Sumatera Utara, Nusa Tenggara Barat, Nusa Tenggara Timur, Kalimantan Barat, kalimantan Tengah, Kalimantan Selatan, Sulawesi Tengah, Sulawesi Selatan, Sulawesi Tenggara, Sulawesi Tenggara, Gorontalo, Sulawesi Barat, Papua Barat, Papua), dan cluster rendah ada 19 yaitu (Sumatera Barat, Riau, Jambi, Sumatera Selatan, Bengkulu, Lampung, Kep. Bangka Belitung, Kep. Riau, Dki Jakarta, Jawa Barat, Jawa Tengah, DI Yogyakarta, Jawa Timur, Banten, Bali, Kalimantan Timur, Kalimantan Utara, Sulawesi utara, Maluku Utara).

Keywords

• k-means algorithm
• toddler
• bps
• province
• data mining