空间误差模型分析印度尼西亚的发病率

Irma Yahya, B. Abapihi, Makkulau Agusrawati, G. A. Wibawa
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摘要

发病率是指一个人不能进行日常活动的一种疾病状态或症状。发病率因人和地区而异。本文旨在调查影响印度尼西亚各省发病率的因素。利用应用空间误差模型(SEM)分析了空间对研究因子的影响。结果表明,扫描电镜可以很好地应用于印度尼西亚的发病率数据。结果表明,到2020年,爪哇岛各省和苏拉威西岛的一些省份存在需要解决的健康问题,因为它们属于高发病率和中高发病率类别。Moran指数的值为正,表明相邻省份的发病率百分比相似。印度尼西亚大多数省份的发病率受到平均上学时间、医疗保险和人口密度的影响。SEM模型的决定系数(R2)为77.60%,可以说是一个比较好的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Error Model to Analyze Morbidity Rate in Indonesia
Morbidity is a diseased state or symptom in which a person is unable to do daily activities. The morbidity rates can differ by person and place. This paper aims to investigate factors affecting morbidity rates in each province in Indonesia. Using applied spatial error model (SEM), this study analyzed the spatial effect on factors being investigated. It demonstrated that SEM is well-applied on Indonesian morbidity rates data. The results show that in 2020, provinces on Java Island and some provinces on Sulawesi Island have health problems that need to be addressed because they are in the high and moderately high morbidity categories. The value of the Moran Index is positive, indicating a similarity in the percentage of morbidity rates in adjacent provinces. The morbidity rates in most of provinces in Indonesia are affected by the duration averages of school attendance, health insurance, and population density. The coefficient of determination (R2) of the SEM model of 77.60% can be said to be a fairly good model.
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