Abstract
This research is aim to determine the comparison of logistic regression models and models Geographically Weighted Logistic Regression and the factors that significantly affect the risk of pneumonia in toddlers in East Java Province. Logistic regression is a statistical analysis that is used to describe the response variable is categorical with the independent variables are categorical or continuous. The main problem of this method if it’s applied in data that is affected of geographic location or spatial data. One of many method to solve the spatial data is Geographically Weighted Logistic Regression (GWLR). GWLR is a statistical method for analyze the data to account for spatial factor. The results showed that there are no significant differences between the logistic regression model with GWLR model. Factors that significantly affect the risk of pneumonia in toddlers in East Java Province is the percentage of low birth weight, the percentage of toddlers who get measles immunization, the percentage of toddlers who get vitamin A, and the percentage of toddlers who get DPT+HB immunization.
Highlights
This research is aim to determine the comparison of logistic regression models and models Geographically Weighted Logistic Regression and the factors that significantly affect the risk of pneumonia in toddlers in East Java Province
The results showed that there are no significant differences between the logistic regression model with Geographically Weighted Logistic Regression (GWLR) model
Jurnal Sains dan Seni ITS, vol 1
Summary
Penyakit pneumonia merupakan salah satu penyebab dari kesakitan dan kematian pada anak di seluruh dunia. Dari penelitian tersebut dapat disimpulkan bahwa model GWLR dengan pembobot adaptive bisquare kernel dan pembobot bisquare kernel merupakan model terbaik untuk mengatasi adanya permasalahan faktor spasial atau lokasi geografis, karena memiliki nilai Akaike Infornation Criterion (AIC) yang lebih kecil dibandingkan model regresi logistik, dan penelitian tentang penyakit pneumonia pernah dilakukan oleh Santoso, et al.[7] yaitu tentang faktor-faktor eksternal pneumonia pada balita di Jawa Timur dengan pendekatan Geographically Weighted. GWR merupakan suatu model regresi sederhana yang memperhitungkan faktor lokasi pengamatan dan menghasilkan penduga parameter model yang bersifat lokal untuk setiap titik dimana data tersebut diamati (Fotheringham, et al [3]). Berdasarkan uraian di atas, maka akan dilakukan analisis dengan menggunakan pendekatan GWLR untuk mendapatkan perbandingan model regresi logistik dengan model GWLR dan mengtahui faktor-faktor yang mempengaruhi risiko penyakit pneumonia pada balita tiap kabupaten/kota di Provinsi. Jika nilai CV semakin kecil maka akan didapatkan bandwidth yang optimum
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