Model Regresi Logistik Spasial

(Studi Kasus: Penyebaran Penyakit Tuberkulosis Paru di setiap Kelurahan di Kota Samarinda pada Tahun 2013)

  • Tiara Nurul Ma’ala Mahasiswa Program Studi Statistika FMIPA Universitas Mulawarman
  • Desi Yuniarti Dosen Program Studi Statistika FMIPA Universitas Mulawarman
  • Memi Nor Hayati Dosen Program Studi Statistika FMIPA Universitas Mulawarman

Abstract

Logistic regression modeling procedure is applied to model the response variable (Y) which is based on one or more categorical explanatory variable (X) which is categorical or continuous. In the application of logistic regression is often found that there are spatial influences that affect the model. The existence of spatial relationships between regions that cause necessary to accommodate the spatial diversity into the model, so that the analysis used logistic regression spatial. First law of geography says that everything is related to everything else, but near things are more related than distant things. Then, when a region becomes a major cause of the spread of a disease is suspected, the region will provide the spread of a disease to the new area adjacent to it. The way to find out the adjacent area with the same characteristics can be done with spatial logistic regression method.The spread of TB disease in Samarinda City is quite high. TB is a chronical disease which has been known by the public and feared of its infection. This study’s aim is to determine the appropriate model to estimate the spread of TB disease. From this model it is known that the factors that influence the number of people with TB disease in every village in Samarinda City in the year 2013 are the number of primary school in every village and the spatial effect. This means that there is the influence of spatial factors to the spread of TB disease in every village in Samarinda City in the Year 2013.

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Published
2017-12-21
How to Cite
MA’ALA, Tiara Nurul; YUNIARTI, Desi; HAYATI, Memi Nor. Model Regresi Logistik Spasial. EKSPONENSIAL, [S.l.], v. 7, n. 2, p. 129-138, dec. 2017. ISSN 2798-3455. Available at: <https://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/60>. Date accessed: 30 apr. 2024.
Section
Articles