Analisis Geographically Weighted Regression (GWR) Berbasis Pemetaan pada Jumlah Menara Telepon Seluler di Kabupaten Lombok Tengah Tahun 2021

Cell towers are tall structures where telecommunications equipment and antennas are installed to support cellular networks. This research aims to analyze the influence of Population Size (X1) and the Number of Service Operators (X2) on the Number of Cellular Phone Towers (Y ) in 139 villages in Central Lombok Regency in 2021. The Geographically Weighted Regression (GWR) method is used to understand spatial variability in the relationship between variables (X1) and (X2) with respect to variable Y . This method is an advancement of the OLS regression analysis method, taking spatial variability into account. By using this method, it is hoped that more accurate spatial distribution patterns can be identified, along with solutions that can assist in the planning of telecommunications infrastructure development in this area. The analysis results indicate that there is significant spatial variability in the distribution of the number of cellular towers based on the Breusch-Pagan test. The significance test results for the parameters show that only the Population Size variable (X1) has a significant effect on the Number of Cellular Towers (Y ) across all observation units (villages) in Central Lombok Regency. The comparison of models shows that the GWR model for the Number of Cellular Towers is better than the OLS Regression, with lower AIC and SSE values and a higher coefficient of determination (R2).

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Publication Details

Journal
Jambura Journal of Probability and Statistics
Published
2025-05-31
DOI
https://doi.org/10.37905/jjps.v6i1.24770
Primary Topic
Economic Growth and Fiscal Policies
Type
article
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article

Analisis Geographically Weighted Regression (GWR) Berbasis Pemetaan pada Jumlah Menara Telepon Seluler di Kabupaten Lombok Tengah Tahun 2021

Siti Hariati Hastuti, Rana Ambarwati Wati, Izu Izatul Febiana
Jambura Journal of Probability and Statistics
Economic Growth and Fiscal Policies
article

Analisis Geographically Weighted Regression (GWR) Berbasis Pemetaan pada Jumlah Menara Telepon Seluler di Kabupaten Lombok Tengah Tahun 2021

Siti Hariati Hastuti, Rana Ambarwati Wati, Izu Izatul Febiana
article en

Abstract

Cell towers are tall structures where telecommunications equipment and antennas are installed to support cellular networks. This research aims to analyze the influence of Population Size (X1) and the Number of Service Operators (X2) on the Number of Cellular Phone Towers (Y ) in 139 villages in Central Lombok Regency in 2021. The Geographically Weighted Regression (GWR) method is used to understand spatial variability in the relationship between variables (X1) and (X2) with respect to variable Y . This method is an advancement of the OLS regression analysis method, taking spatial variability into account. By using this method, it is hoped that more accurate spatial distribution patterns can be identified, along with solutions that can assist in the planning of telecommunications infrastructure development in this area. The analysis results indicate that there is significant spatial variability in the distribution of the number of cellular towers based on the Breusch-Pagan test. The significance test results for the parameters show that only the Population Size variable (X1) has a significant effect on the Number of Cellular Towers (Y ) across all observation units (villages) in Central Lombok Regency. The comparison of models shows that the GWR model for the Number of Cellular Towers is better than the OLS Regression, with lower AIC and SSE values and a higher coefficient of determination (R2).

Jambura Journal of Probability and StatisticsVol. 6(1)
Openalex Percentile: Top 77%
Economic Growth and Fiscal Policies
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Analisis Geographically Weighted Regression (GWR) Berbasis Pemetaan pada Jumlah Menara Telepon Seluler di Kabupaten Lombok Tengah Tahun 2021 — Siti Hariati Hastuti, Rana Ambarwati Wati, et al. · Jambura Journal of Probability and Statistics (2025) | TGRS Research Map | TGRS