Abstract
Nutritional problems in toddler are still a serious problem in various districts/cities in Indonesia. The case of malnutrition in Bali Province vary in many regions and hypothesized to be influenced by geographic location, which is often known as spatial heterogeneity. To overcome this problem, a spatial regression method is used on this research. This study aims to model the factors that are hypothesized affect malnourished toddlers in Bali Province using spatial regression methods, i.e. spatial autoregressive model (SAR) and spatial error model (SEM). Both models have 5 predictors variable, i.e. the percentage of toddlers aged between 6 - 59 months who received vitamin A, the percentage of babies with low birth weight (LBW), the percentage of households with clean and healthy living behavior (PHBS), the percentage of children under five receiving exclusive breastfeeding, and the percentage of toddler health services, which are obtained from Bali Provincial Health Office. The results showed SEM method produced smaller AIC value and higher , with and AIC values ??of 96.24% and 60.84, respectively.
Highlights
Nutritional problems in toddler are still a serious problem in various districts/cities in Indonesia
This study aims to model the factors that are hypothesized affect malnourished toddlers in Bali Province using spatial regression methods, i.e. spatial autoregressive model (SAR) and spatial error model (SEM)
The results showed SEM method produced smaller AIC value and higher, with and AIC values of 96.24% and 60.84, respectively
Summary
Salah satu permasalahan yang dihadapi terkait status gizi yaitu gizi buruk. Gizi buruk merupakan suatu kondisi kurangnya nutrisi pada tubuh atau nutrisinya di bawah standar. Mencermati hal ini, model angka gizi buruk pada balita di Provinsi Bali dibuat dengan menggunakan metode regresi spasial yang merupakan pengembangan dari metode analisis regresi linier, di mana aspek lokasi juga diperhatikan. SAR adalah model regresi spasial yang mengasumsikan variabel terikat pada suatu wilayah dipengaruhi oleh variabel terikat di wilayah lainnya dalam model (terdapat korelasi spasial pada variabel terikat). Sedangkan SEM mengasumsikan bahwa pada error model suatu wilayah dengan wilayah lainnya terdapat korelasi spasial (LeSage & Pace, 2009). Regresi spasial merupakan salah satu metode statistika yang digunakan untuk mengetahui hubungan antara variabel dependen dan variabel independen dengan mempertimbangkan ketergantungan spasial.
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