PENERAPAN ALGORITMA C4.5 UNTUK DIAGNOSA STATUS GIZI PADA ANAK BALITA BERBASIS WEBSITE

Abstract

Nutritional status of infants is an important factor that must be considered since
infancy is a period of development with a range of nutrients. Nutritional status
can be divided into three indicators of good nutrition, malnutrition and
malnutrition. C4.5 classification algorithm is an algorithm that can produce
easily interpreted decision tree, have an acceptable level of accuracy, efficient in
handling discrete and numeric-type attributes (Kamagi dan Seng, 2014).
Therefore, in this study will be conducted data analysis nutritional status in
children under five using the classification of the data mining algorithm C4.5
using four variabels: gender, age (months), weight (kg) and height (cm). Based on
these descriptions, we need a system that can represent an expert who has the
knowledge base and experience of diarrheal disease, which is an expert system.
From 108 infants amount of data that consists of 92 data subject to a good
nutrition and 16 data were experiencing malnutrition among children under five
are obtained from Posyandu Nyangkowek, then obtained 17 rules resulting from
C4.5 decision tree algorithm with good nutrition as class numbers 12 and the
number of undernourished class so much as 5 rules, so that it can be concluded
that the research that is implemented into a web application can help users,
particularly parents in diagnosing the nutritional status of children under five.