Geospatial intelligence framework for BTS infrastructure planning toward universal internet access target in Indonesia

• Random Forest algorithm used for BTS development suitability index. • Predictors: environment, infrastructure readiness, and fiber optic coverage. • BTS development priorities identified by integrating suitability and internet demand. • Provides a reference for equitable internet coverage in countries worldwide. Equitable internet coverage has emerged as a key global priority, which is essential for promoting inclusive and sustainable development. The Indonesian government aims to provide universal internet access by 2024, particularly in remote regions. This study introduces a novel machine-learning-based approach to identify the priority areas for deploying Base Transceiver Station (BTS) towers, which are crucial for achieving the internet access targets of the government. A BTS Network Priority Index was developed by integrating the internet demand estimates with a BTS suitability index derived from key predictors: proximity to fiber optic stations, physical–environmental suitability, and infrastructure–economic readiness. The model identified areas with high internet demand and high BTS suitability as the most critical for immediate development, covering 20 km 2 . Additionally, future BTS development should target areas with high demand but medium suitability (900 km 2 ) and medium demand but high suitability (280 km 2 ). To validate the methodology, the Random Forest model was employed, which achieved an area under the curve value of 0.7315, indicating strong predictive performance. For the BTS Deployment Suitability parameter, the median was 0.65, with the lower and upper quartiles at 0.44 and 0.85, respectively, confirming that most proposed locations are highly suitable for development. This systematic approach provides data-driven insights for the equitable distribution of BTS towers to ensure efficient internet infrastructure expansion across Indonesia. Furthermore, the study offers a framework that can be adapted by other countries aiming to improve their digital infrastructure and achieve comprehensive, equitable internet access.

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Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2024-11-19
DOI
https://doi.org/10.1016/j.jag.2024.104274
Citations
2
Primary Topic
ICT Impact and Policies
Type
article
Field-Weighted Citation Impact
0.64
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article

Geospatial intelligence framework for BTS infrastructure planning toward universal internet access target in Indonesia

Wervyan Shalannanda, Arie Wahyu Wijayanto, Pitri Rohayani, Fabian Surya Pramudya et al.
2 citations
International Journal of Applied Earth Observation and Geoinformation
ICT Impact and Policies
0.64
article

Geospatial intelligence framework for BTS infrastructure planning toward universal internet access target in Indonesia

Wervyan Shalannanda, Arie Wahyu Wijayanto, Pitri Rohayani, Fabian Surya Pramudya, Rezzy Eko Caraka, Ismail Al Faruqi, Anjar Dimara Sakti, I Gusti Ayu Andani, Cokro Santoso, Muhammad Rizky Zakiar, Anissa Dicky Putri, A Setiyadi
article en
2 citations

Abstract

• Random Forest algorithm used for BTS development suitability index. • Predictors: environment, infrastructure readiness, and fiber optic coverage. • BTS development priorities identified by integrating suitability and internet demand. • Provides a reference for equitable internet coverage in countries worldwide. Equitable internet coverage has emerged as a key global priority, which is essential for promoting inclusive and sustainable development. The Indonesian government aims to provide universal internet access by 2024, particularly in remote regions. This study introduces a novel machine-learning-based approach to identify the priority areas for deploying Base Transceiver Station (BTS) towers, which are crucial for achieving the internet access targets of the government. A BTS Network Priority Index was developed by integrating the internet demand estimates with a BTS suitability index derived from key predictors: proximity to fiber optic stations, physical–environmental suitability, and infrastructure–economic readiness. The model identified areas with high internet demand and high BTS suitability as the most critical for immediate development, covering 20 km 2 . Additionally, future BTS development should target areas with high demand but medium suitability (900 km 2 ) and medium demand but high suitability (280 km 2 ). To validate the methodology, the Random Forest model was employed, which achieved an area under the curve value of 0.7315, indicating strong predictive performance. For the BTS Deployment Suitability parameter, the median was 0.65, with the lower and upper quartiles at 0.44 and 0.85, respectively, confirming that most proposed locations are highly suitable for development. This systematic approach provides data-driven insights for the equitable distribution of BTS towers to ensure efficient internet infrastructure expansion across Indonesia. Furthermore, the study offers a framework that can be adapted by other countries aiming to improve their digital infrastructure and achieve comprehensive, equitable internet access.

International Journal of Applied Earth Observation and GeoinformationVol. 135
Bandung Institute of Technology (ID), Binus University (ID), Universitas Komputer Indonesia (ID), Badan Pusat Statistik (ID), Research Organization of Information and Systems (JP), Telkom University (ID)
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
ICT Impact and Policies
0.64
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