SISTEM PENDUKUNG KEPUTUSAN PENENTUAN STATUS GIZI BALITA PADA DINAS KESEHATAN KABUPATEN ALOR MENGGUNAKAN ALGORITMA C4.5

Abstract

Assessment of nutritional status plays a very important role in monitoring children's nutrition. If the assessment of nutritional status is carried out correctly and accurately, signs or symptoms of impaired growth and development in children can be identified early so that mitigation and prevention can be carried out in an effort to improve the nutritional status of children under five. And the occurrence of nutritional problems can be minimized. For this reason, determining the nutritional status of toddlers must be done quickly and accurately. Puskesmas as the technical implementer of the Health Service, has the main task of collecting data and assessing the nutritional status of toddlers and submitting the results of the assessment to the Health Service. The determination of nutritional status that has been carried out is by looking at and calculating the standard anthropometric table for assessing the nutritional status of toddlers according to the Decree. Minister of Health Number: 1995/Menkes/SK/XII/2010. However, Puskesmas are often slow in treating large numbers of patients and also have limited resources, especially in areas where there is a shortage of medical personnel. So this also influences the results of the assessment of determining the nutritional status of toddlers. For this reason, the Health Service needs to provide an optimal method for determining the nutritional status of toddlers to be used by Community Health Centers to determine the nutritional status of toddlers quickly, precisely and accurately. So researchers have conducted research and produced a decision support system for determining nutritional status in toddlers using the C4.5 algorithm. Test results to measure algorithm performance using the Confusion Matrix, Accuracy, Precision and Recall testing method, it is known that the C4.5 algorithm has an accuracy value of 72.13 %, Precision value 71.43% and Recall value 22.73% Keywords : Decision Support, Nutritional Status, Toddlers, C4.5 Algorithm