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Please use this identifier to cite or link to this item: http://repository.uksw.edu/handle/123456789/13377
Title: Analysis on the Comparison Exponential Smoothing and Neural Network in Forecasting The Trend of Toddler Nutritions in Community Health Centre
Authors: Santoso, Agustinus Budi
Keywords: exponential smoothing;neural network backpropagation;peramalan;eviews;matlab
Issue Date: 2017
Publisher: Magister Sistem Informasi Program Pascasarjana FTI-UKSW
Abstract: Puskesmas merupakan layanan bidang kesehatan yang memberikan pelayanan terpadu, konsultasi dan pelayanan balita. Terdapat asumsi bahwa faktor usia balita, status ekonomi mempengaruhi peningkatan gizi balita. Metode Exponential Smoothing digunakan meramalkan data time series dengan mengalami pola kerandoman pada trend data. Tujuan penggunaan Exponential Smoothing dan Neural Network sebagai analisa peramalan pada peningkatan gizi balita. Pedoman status gizi didapatkan dari Z-Score sesuai standar KEMENKES dengan golongan gizi berdasarkan usia balita, berat badan. Peramalan tersebut dihubungkan dengan asumsi pengaruh faktor status ekonomi, pendidikan orang tua, status asuh terhadap status gizi. Analisa peramalan dari metode Exponential Smoothing dengan Eviews, dan analisa peramalan metode Neural Network Backpropagation dengan Matlab sebagai perbandingan untuk menentukan peramalan terbaik untuk 3 bulan berikutnya berdasarkan pola trend data sebelumnya. Hasil analisa peramalan digunakan untuk sarana peramalan status gizi balita yang tersedia dalam model grafik dan sarana analisa anggota Puskesmas untuk evaluasi peningkatan gizi balita.
In Indonesia, community health centres (a.k.a Puskesmas) provide integrated services and consultations for the communities, including toddler care services. There is an assumption that the increase of toddler’s nutrition status is influenced by toddler’s age and parents’ economic status. In this study, the exponential smoothing and the neural network methods were used to forecast toddler’s nutrition status. The forecastings were then used to test the assumption whether toddler’s nutrition status may be influenced by parents’ economic status, education, and care status. The forecasting by exponential smoothing with Eviews method and Neural Network Backpropagation method with Matlab were analyzed and compared to determine which forecasting was best for the next three months based on the pattern of the previous trend data. The results of analysis are used to facilitate and assist community health centre officers in forecasting and evaluating the increase in toddler’s nutrition status.
URI: http://repository.uksw.edu/handle/123456789/13377
Appears in Collections:T2 - Master of Information Systems

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