Penerapan Data Mining Dengan Algoritma Neural Network Pada Sistem Informasi Prediksi Kasus Balita Gizi Buruk Di Provinsi Nusa Tenggara Barat

Abstract

One of the main objectives of national development is to improve the quality of human resources sustainably. This effort begins with a majors focus on the child's development from conception to adulthood. During this period of growth, the fulfillment of children's basic needs such as care and nutritious food to make them healthy, intelligent, and productive human resources. The case of malnutrition among toddlers and children is one of the priority issues handled by the government. Although from year to year there is a decrease in the number of children with malnutrition, the incidence rate in Indonesia is still high compared to other developing countries. Malnutrition is a condition caused by low consumption of energy and protein in daily food intake so that it does not meet the Nutritional Adequacy Rate (RDA). West Nusa Tenggara (NTB) is a province with high cases of malnutrition, namely 29.5% above the tolerance limit set by WHO, which is 20% of the total number of children under five. Data from the NTB Health Office states that in 2018 there were 217 cases of malnutrition spread across ten districts/cities. In this study, the authors researched the distribution and factors causing malnutrition in the West Nusa Tenggara (NTB) region. The data processed in this study comes from the website of the Central Bureau of Statistics (BPS) NTB which is processed using the Neural Network algorithm to produce predictive information on cases of malnutrition in the 2014-2017 period in NTB Province

Prediksi PREDIKSI TINGKAT OBESITAS MENGGUNAKAN NEURAL NETWORK: PENDEKATAN KLASIFIKASI BINER

“…Keunggulan utama dari jaringan saraf tiruan adalah kemampuannya untuk menangani masalah-masalah yang sulit didefinisikan dengan baik atau memiliki struktur yang kompleks [4]. Penggunaan Neural Network telah banyak dilakukan dalam menganalisis data seperti analisis geospasial kasus Stunting [10], prediksi Jantung Koroner [11], klasifikasi paket jaringan [12], prediksi kasus balita Gizi buruk [13], prediksi dan analisa penyakit Diabetes Metitus [14], dari beberapa penelitian tersebut terlihat bahwa penggunaan Neural Network memiliki hasil yang baik.…”