Equal Access to the Internet Among Schools Across Subdistricts as the Basis for Local Government Policies on Digital Educational Infrastructure Development

Aiman Sabar Rezeky; Andi Rahmat Nizar Hidayat

doi:10.26740/jpus.v10n2.p167-180

Authors

Aiman Sabar Rezeky Universitas Negeri Makassar
Andi Rahmat Nizar Hidayat Universitas Negeri Makassar

DOI:

https://doi.org/10.26740/jpus.v10n2.p167-180

Keywords:

Blank Spot, Digital Divide, Educational Services, Gowa Regency, School Internet Access Ratio

Abstract

The digitization of educational services requires equitable internet access across all educational institutions. However, high access coverage does not necessarily indicate equitable service distribution at the regional level. This study aims to analyze the equity of internet access in elementary schools and junior high schools in Gowa Regency, identify subdistricts with the highest disparities, and analyze the relationship between the number of schools and the level of internet dead zones. The study employs a quantitative descriptive approach with a comparative analysis across subdistricts. Data were obtained from the Gowa Regency Education Office in 2026 and cover all 562 schools across 18 subdistricts. The analysis was conducted using the School Internet Access Ratio, blank spot rates, descriptive statistics, Spearman’s correlation, and the Mann-Whitney test. The results showed that school internet access in Gowa Regency was relatively high, with an aggregate coverage rate of 97.33 percent and an average across subdistricts of 96.89 percent. However, as many as 15 schools (2.67 percent) still do not have internet access, and all of them are concentrated in six subdistricts. The Tinggi Moncong subdistrict has the highest blank spot rate, at 12.90 percent. The results showed a weak association between the number of schools and the blank spot rate (Spearman’s rho = 0.119; p = 0.637). The Mann–Whitney test also showed no statistically significant difference in the number of schools between subdistricts with blank spots and those with full access (U = 32.0; p = 0.743). Because the analysis covered all 18 subdistricts, these p-values are reported as supplementary measures of the observed patterns rather than as evidence for generalization from a sample to a wider population. The results of the analysis show that the number of schools has no significant relationship with the level of blank spots (Spearman’s rho = −0.119; p = 0.637), while the difference in the number of schools between subdistricts with blank spots and those with full access is also not significant (p = 0.743). These findings indicate that, although aggregate school internet coverage is high, remaining access gaps are concentrated in a limited number of subdistricts and schools. This pattern has policy implications for more targeted interventions at the school level. Therefore, policies should focus on school-based targeting, strengthening interagency coordination, improving the connectivity database, and conducting regular monitoring of access.

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