Pemodelan Kejadian Balita Stunting di Kabupaten Bojonegoro dengan Metode Geographically Weighted Regression dan Multivariate Adaptive Regression Splines

Abstract

Toddler stunting is a chronic nutritional problem caused by one of which is inadequate nutritional intake in infants. Bojonegoro is a district in East Java province where the incidence of stunting under five is still common. In this study, we will compare the incidence of stunting under five in Bojonegoro district using GWR and MARS. GWR is able to model cases for each region spatially, while MARS is able to model cases without considering the pattern of relationships between predictor variables and response variables. The best GWR model selected the smallest CV and MSE values ​​and the largest R-Square values. The best model of the Adaptive Bi-Square kernel function was obtained with a bandwidth of 28, the value of CV=2.4635, MSE=0.8620, and R-Square=0.8734. The best MARS model selected the smallest GCV value and the largest R-Square. From the combination of MO, BF and MI values, the best model was obtained at BF=24, MI=1 and MO=1 with GCV=1,29144 and R-Square=0,841 values. Comparing the two models, the MARS model is better because the R-Square value of the GWR model is greater than the MARS although the numerical value is not much different, while the MSE value of the MARS model is smaller than the MSE value of the GWR model with a much different difference. The results of this study will provide knowledge in the form of a regression model for the Bojonegoro district health office in predicting predictor variables that affect the incidence of stunting under five in Bojonegoro district.

Hybrid K Means-Multivariate Adaptive Regression Splines for Distribution of Dengue Fever Risk Mapping in Bojonegoro District

“…Forward stepwise is used to obtain the number of basis functions and backward stepwise is used to obtain a simple model by eliminating the basis functions that have a small contribution to the response variable [11]. The MARS model chosen is the one that has a minimum GCV with the following formula [28] [29].…”

Penerapan Multivariate Adaptive Regression Splines Untuk Analisis Faktor Yang Mempengaruhi Kelayakan Nasabah Yang Mengajukan Pembiayaan

“…Sehingga pada penelitian ini akan menggunakan metode Multivariate Adaptive Regression Splines (MARS) untuk mendapatkan karakteristik nasabah yang layak dan tidak layak mendapatkan pembiayaan di BSI kantor cabang Bojonegoro. MARS merupakan salah satu metode nonparametrik modern untuk pemodelan yang memiliki kemampuan estimasi yang tinggi (A. Y. K. Kartini & Ummah, 2022).…”