REGRESI LINIER BERGANDA DAN SPATIAL DURBIN MODEL UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI GIZI BURUK BALITA DI KOTA MEDAN
DOI:
https://doi.org/10.24114/jmk.v4i1.11017Abstract
ABSTRAKKasus gizi buruk di kota Medan terus mengalami peningkatan dibandingkan dengan tahun-tahun sebelumnya. Pada tahun 2015, Kota Medan berada pada peringkat ke-2 kasus gizi buruk balita terbanyak di Sumatera Utara. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang mempengaruhi gizi buruk balita di kota Medan dan menentukan model terbaik yang dapat menggambarkan gizi buruk balita di kota Medan. Analisis yang digunakan adalah regresi linier berganda dengan Ordinary Least Square (OLS) dan Spatial Durbin Model (SDM). Berdasarkan analisis Moran™s I, diperoleh adanya dependensi spasial pada variabel angka gizi buruk balita di kota Medan serta beberapa faktor yang mempengaruhinya. Dengan demikian perlu dilakukan analisis spasial model SDM. Dari hasil penelitian, diperoleh model SDM menghasilkan R-square sebesar 0.703 dan AIC sebesar 117.2534. variabel yang secara signifikan mempengaruhi gizi buruk balita di kota Medan dengan model SDM adalah banyaknya balita yang mendapat imunisasi lengkap dan banyaknya rumah tangga miskin Kata kunci : gizi buruk, dependensi spasial, Spatial Durbin Model, Ordinary Least Square ABSTRACTCases of malnutrition in the city of Medan continues to increase compared with previous years. In 2015, the city of Medan is ranked 2nd malnutrition of children under five in North Sumatra. This study aims to identify factors that affect infant malnutrition in the city of Medan and determine the best model to describe malnourished children under five in the city of Medan. The analysis used is multiple linear regression with ordinary least squares (OLS) and Spatial Durbin Model (SDM). Based on the analysis of Moran's I, obtained their spatial dependencies in the variable infant malnutrition rate in the city of Medan as well as some of the factors that influence it. Thus the need to analyze the spatial model of HR. From the research results, obtained SDM models produce R-square of 0703 and AIC at 117.2534. variables that significantly affect malnourished children under five in the city of Medan with human models is the number of infants are fully immunized and the number of poor households . Keywords: malnutrition, spatial dependencies, Spatial Durbin Model, Ordinary Least SquareDownloads
Published
2018-04-02
Issue
Section
Articles
License
This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Penulis.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).