Modeling Life Expectancy in Central Java Using Spatial Durbin Model

Hakim, Arief Rachman; Yasin, Hasbi; Rusgiyono, Agus

doi:10.14710/medstat.12.2.152-163

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…Lalu, untuk Persentase rumah tangga berperilaku hidup bersih dan sehat (𝑋 2 ) dan Jumlah posyandu (𝑋 3 ) tidak terdapat autokorelasi antar lokasi. Nampak pada variabel respon terdapat autokorelasi, sedangkan pada variabel prediktor terdapat 3 variabel yang memiliki autokorelasi dimana memenuhi syarat yaitu minimal satu variabel prediktor memiliki autokorelasi sehingga seluruh variabel penelitian dapat dimodelkan menggunakan regresi spatial durbin model (SDM) dapat digunakan berdasarkan [9].…”

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Pemodelan Umur Harapan Hidup di Jabar Tahun 2021 Menggunakan Spatial Durbin Model

Ratih Nurfitri,

Teti Sofia Yanti

2023

JRS

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Abstract. Linear regression analysis is a technique in statistics to form a model of the relationship between response variables with one or more predictor variables, but linear regression becomes less specific if the data used has a location aspect because the modeling does not take into account the proximity factor between regions. Therefore there was a development of linear regression into spatial regression where the location aspect is also considered, one of the spatial regression analysis is spatial Durbin Model (SDM) or a type of spatial regression analysis that considers the influence of the proximity of the region on the response variables and predictor variables. In this study, life expectancy modeling will be carried out to determine the factors that affect life expectancy in West Java province in 2021 with the predictive variables being the average length of school, the percentage of households behaving clean and healthy, the number of Posyandu, the percentage of poor people and adjusted per capita expenditure. From the results of the study, the factors that have a significant effect on life expectancy are the average length of schooling and the percentage of adjusted per capita expenditure, with the value of the coefficient of determination (R2) is 73.002 % which can be interpreted that the life expectancy model in West Java in 2021 can be explained by the model of 73.002%, while. Abstrak. Analisis regresi linier adalah teknik dalam statistika untuk membentuk model hubungan antara variabel respon dengan satu atau lebih variabel prediktor, namun regresi linier menjadi kurang spesifik jika data yang digunakan memiliki aspek lokasi karena dalam pemodelannya tidak memperhitungkan faktor kedekatan antar wilayah. Oleh karena itu terjadilah pengembangan regresi linier menjadi regresi spasial dimana aspek lokasi juga ikut diperhatikan, salah satu analisis regresi spasial adalah Spatial Durbin Model (SDM) atau jenis analisis regresi spasial yang memperhatikan pengaruh kedekatan daerah pada variabel respon maupun variabel prediktornya. Pada penelitian ini akan dilakukan pemodelan Umur Harapan Hidup untuk mengetahui faktor-faktor yang mempengaruhi Umur Harapan Hidup yang ada di provinsi Jawa Barat pada tahun 2021 dengan variabel predikornya adalah Rata-rata Lama Sekolah, Persentase Rumah Tangga Berperilaku Hidup Bersih dan Sehat, Jumlah Posyandu, Persentase Jumlah Penduduk Miskin dan Pengeluaran Perkapita yang Disesuaikan. Dari hasil penelitian, faktor-faktor yang berpengaruh signifikan terhadap umur harapan hidup adalah rata-rata lama sekolah dan persentase pengeluaran perkapita yang disesuaikan, dengan nilai koefisien determinasi (R2) adalah 73,002 % yang dapat diartikan bahwa model umur harapan hidup di Jawa Barat tahun 2021 dapat dijelaskan oleh model sebesar 73,002%, sedangkan sisanya 26.998% dijelaskan oleh variabel lain diluar model.

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Section: /146unclassified

Pemodelan Umur Harapan Hidup di Jabar Tahun 2021 Menggunakan Spatial Durbin Model

Ratih Nurfitri,

Teti Sofia Yanti

2023

JRS

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“…The value chain spillover effects and the spatial spillover implications of innovation efficiency were investigated by (Huang) [10] using the geographical Durbin model. According to, (Hakim et al) [9] Many creative fields actually benefit from "local knowledge spillovers", as was shown in earlier research. Migration is often used to transfer information across geographical locations.…”

Section: Literature Reviewmentioning

confidence: 85%

The Construction of Economic Education Model Based on the Spatial Durbin Model

Xiao Li

2024

jes

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This research attempts to address the complexities and the nuances that are a part of the economic education by proposing an innovative model that is grounded in the Spatial Durbin Model (SDM). The spatial interdependencies which are crucial for the understanding of the regional variations in the economic implications and the efficacy of the educational policies are sometimes neglected by the conventional main frames of the economic education. The integration of the SDM, which is a sophisticated spatial econometric tool, aims to offer a thorough and detailed understanding of the intricate relationships between the education and the economic development in context of the diverse geographics. The model that is proposed in this research study extends beyond the traditional linear regressions as it accounts for the spatial autocorrelation and the spatial lag effects which thereby captures the spatial spillover and the diffusion of the educational investments and policies. With the help of the empirical analysis which moves forward by the utilization of the spatial econometric techniques such as the spatial lag and the spatial error models, strives to explore the spatial dynamics of the economic education while identifying the spatial patterns, the dependencies involved and the disparities that come up in the attainment of the educational and the economic performance. By incorporation of the spatial dimensions into the economic education model, the policymakers and the educators are able to get their hands on the in depth insights. This is into the spatially differentiated impacts of the educational interventions which tends to enable a more targeted and a more effective design and implementation of the policy. Furthermore, the proposed model also aims to facilitate the identification of the spatially targeted strategies in order to address the regional disparities with respect to the educational outcomes and the economic growth. Hence, it contributes to a more inclusive and a sustainable development trajectory. Through the interdisciplinary effort of bridging the economics, education and the spatial analysis, this research extends a valuable main frame for the policymakers, educators and the researchers which helps in attaining better understanding and helps to address the multifaceted challenges as well as the opportunities in the economic education and the regional development. Ultimately, this has enhanced the understanding of the spatial dimensions of the economic education which leads to the evidence based policies and interventions which are aimed at nurturing the equitable and resilient economic growth. In this paper, we utilize the spatial Durbin model as a framework to investigate the role that advanced degrees play in driving technological innovation in various parts of the world. Spatial self-correlation and instability in the geographic distribution of post-graduates in China were shown by data from the regional panel in China between 2004 and 2018. Advanced degrees facilitated the advancement of cutting-edge technologies.

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“…SDM berfungsi untuk menghasilkan estimasi regresi untuk melihat hubungan antara variabel X terhadap variabel Y, serta berdasarkan adanya efek spasial (dependensi spasial) didalamnya (Bivand et al 2013). Model spasial durbin telah diterapkan pada penelitian sebelumnya yakni dari (Ramadani et al 2013), (Hakim et al 2019), (Suaib et al 2022) serta (Taryono et al 2018). Dari penelitian tersebut dapat diketahui bahwa terdapat beberapa variabel prediktor yang mempengaruhi secara signifikan sekaligus diperoleh keterkaitan antar daerah yang berdekatan terhadap kasus yang diteliti (dependensi spasial).…”

Section: Pendahuluanunclassified

Penerapan Model Spasial Durbin Dengan Uji Lanjutan Local Indicator of Spatial Autocorrelation Untuk Melihat Penyebaran Stunting Di Kabupaten Bone Bolango

HASIRU¹,

DJAKARIA²,

HASAN³

2022

Jambura J. Probab. Stat.

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One of the spatial regression analysis used is the spatial durbin model (SDM). This model can be applied to obtain the relationship between X and Y variables and their spatial effects. This research was continued by testing the local spatial autocorrelation, namely the local indicator of spatial autocorrelation (LISA) which aims to provide information on the pattern of spatial relationships of each observation area in Bone Bolango regency. Stunting cases in Gorontalo province, especially in Bone Bolango regency, are in a status that needs to be addressed immediately due to the prevalence rate in Bone Bolango regency in 2019 above 20% based on the WHO standard. The results showed that the factors that significantly affected stunting in 2019 in Bone Bolango regency were exclusive breastfeeding, the proper sanitation and poverty. Meanwhile, based on the spatial effect, the factors that significantly affected stunting in 2019 in Bone Bolango regency were the percentage of exclusive breastfeeding, the percentage of LBW, the number of children with CBI and poverty. Based on result from the LISA, the observation areas of stunting cases showed that the percentage of exclusive breastfeeding, the number of children with CBI and povertu had a spatial autocorrelation or forming a grouping on the distribution of the stunting cases, the number of children with IDL and poverty, there are sub-districts that have spatial autocorrelation.

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Modeling Life Expectancy in Central Java Using Spatial Durbin Model

Cited by 5 publications

References 7 publications

Pemodelan Umur Harapan Hidup di Jabar Tahun 2021 Menggunakan Spatial Durbin Model

Pemodelan Umur Harapan Hidup di Jabar Tahun 2021 Menggunakan Spatial Durbin Model

The Construction of Economic Education Model Based on the Spatial Durbin Model

Penerapan Model Spasial Durbin Dengan Uji Lanjutan Local Indicator of Spatial Autocorrelation Untuk Melihat Penyebaran Stunting Di Kabupaten Bone Bolango

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