Chandra, Bobi (2025) Implementasi Algoritma K-Means Clustering Angka Kecukupan Gizi Pangan. Other thesis, Universitas Islam Riau.

Text skripsi_183510775_watermark.pdf - Published Version Restricted to Registered users only Download (5MB) | Request a copy

Abstract

The Nutrient Adequacy Score (NAC) is a standard of nutritional needs used to assess the adequacy of food consumption in a population. However, in practice, the fulfillment of community nutrition still faces various challenges, such as inequality in food distribution, unbalanced diets, and socio-economic factors that affect access to nutritious food. In Indonesia, nutrition problems such as stunting, undernutrition, obesity and diet-related diseases are still serious health issues. In order to understand nutritional consumption patterns and identify community groups with similar nutritional needs, the author as part of academia thought of a system that needed data-based analysis that went deeper into this case. The author also has an idea in the form of an idea to create a program for implementing the K-Mean Clustering Algorithm for Food Nutrition Adequacy Rates from the food composition table from KEMENKES RI (2020) and using the web-based K-Mean Clustering method. The results obtained by doing this method are Euclidean Distance, which is numerical that can be processed in the form of a clustering pattern of a lot of data that was previously randomized into group data, each of which has a value.

Actions (login required)

View Item