在南苏拉威西省的犯罪案件水平上实施了明确无误的空间回归模式

Adiatma Rasyid, Irwan Kasse, Adnan Sauddin
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引用次数: 0

摘要

本研究讨论了南苏拉威西省的犯罪率。有几个主要因素可能导致犯罪,特别是在南苏拉威西省。本研究旨在考察南苏拉威西省犯罪率的空间看似不相关回归SUR (Spatial seem uncorrelation Regression)模型,但由于存在不符合SUR空间分析的假设,因此所得模型仅限于空间自回归(Spatial Autoregressive, SAR)和空间误差模型(Spatial error model, SEM)。所得的SAR模型表明,人口、贫困人口数量和人均GDP对人口受犯罪影响的风险有显著的正影响。得到的SEM模型显示,人口与失业人数之间存在显著的正向影响,失业人数对人口暴露于犯罪的风险存在显著的负向影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Penerapan Model Seemingly Unrealated Regression (SUR) Spasial pada Tingkat Kasus Kriminalitas di Provinsi Sulawesi Selatan
This research conducted discusses the crime rate in South Sulawesi Province. There are several main factors that can lead to crime, especially in South Sulawesi Province. This research was conducted to see the Spatial Seemingly Unrealated Regression SUR) model at the crime rate in South Sulawesi Province, but there are assumptions that do not meet the SUR Spatial Analysis, so the model obtained is limited to the Spatial Autoregressive (SAR) and Spatial Eror Model (SEM). The SAR model obtained shows that the population, the number of poor people, and the GDP per capita have a positive and significant effect on the risk of the population being affected by crime. The SEM model obtained shows a positive and significant effect between the population, the number of unemployed has a negative and significant effect on the risk of the population being exposed to crime.
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