Modelling and Maping Malnutrition Toddlers in Bojonegoro Regency with Mixed Geographically Weighted Regression Approach

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Malnutrition Toddlers in Bojonegoro Regency with Mixed Geographically Weighted Regression Approach</title> <meta name="description" content="Modelling and Maping Malnutrition Toddlers in Bojonegoro Regency with Mixed Geographically Weighted Regression Approach"> <meta name="keywords" content="GWR, MGWR, R2, AIC"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img 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publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Modelling and Maping Malnutrition Toddlers in Bojonegoro Regency with Mixed Geographically Weighted Regression Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elvira%20Mustikawati%20P.H.">Elvira Mustikawati P.H.</a>, <a href="https://publications.waset.org/abstracts/search?q=Iis%20Dewi%20Ratih"> Iis Dewi Ratih</a>, <a href="https://publications.waset.org/abstracts/search?q=Dita%20Amelia"> Dita Amelia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five. <iframe src="https://publications.waset.org/abstracts/2014.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GWR" title="GWR">GWR</a>, <a href="https://publications.waset.org/abstracts/search?q=MGWR" title=" MGWR"> MGWR</a>, <a href="https://publications.waset.org/abstracts/search?q=R2" title=" R2"> R2</a>, <a href="https://publications.waset.org/abstracts/search?q=AIC" title=" AIC"> AIC</a> </p> <a href="https://publications.waset.org/abstracts/2014/modelling-and-maping-malnutrition-toddlers-in-bojonegoro-regency-with-mixed-geographically-weighted-regression-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2014.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">296</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational 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Modelling and Maping Malnutrition Toddlers in Bojonegoro Regency with Mixed Geographically Weighted Regression Approach