Integration of Sentinel Imagery and Geographic Information System for Analysing Spatial Distribution of Senior and Vocational High School Education Facilities in  West Bandung Regency, Indonesia

Hamim Zaky Hadibasyir; Choirul  Amin; Retna Dwi Wulandari; Putri  Maulidianti; Nada Salsabila Firdaus

doi:10.38035/dijms.v6i4.4054

Authors

Hamim Zaky Hadibasyir Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Choirul Amin Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Retna Dwi Wulandari Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Putri Maulidianti Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Nada Salsabila Firdaus Geo-information and Data Analytics (GiDa) Research Group, Sukoharjo, Indonesia

DOI:

https://doi.org/10.38035/dijms.v6i4.4054

Keywords:

Average Nearest Neighbour, Sentinel-2 Imagery, Spatial Distribution of Educational Infrastructure

Abstract

Disparity in the distribution of educational facilities in developing regions is an issue to achieve equity in access to education. For example, access to senior high school (SMA) and vocational high school (SMK) has remained unequal across different sub-districts within West Bandung Regency of Indonesia and will pose a problem in attaining 12 years of compulsory education. In this research, the methods of remote sensing and GIS were integrated for analyzing the spatial distribution and accessibility to senior and vocational high school. Using data from Google Maps in 2021 and Sentinel imagery, the ANN and kernel density methods have been used in identifying the distribution pattern, while conducting buffer analysis to map coverages. In fact, there is a clustered distribution in sub-districts like Lembang, Padalarang, and Cipongkor, with isolated sub-districts like Parongpong and Rongga showing huge accessibility gaps where settlement exists over 7.5 km away from the school. These findings raise awareness of the pressing need for concerted infrastructure planning and investment at sub-national levels in pursuit of equal opportunities that are imperative for sustainable development and social equity in developing countries.

References

Al Kahfi, M., & Widiyastuti, D. (2017). Kajian Ketersediaan Dan Pola Distribusi Fasilitas Pendidikan Sekolah Menengah Atas/Sederajat Di Kabupaten Karanganyar. Jurnal Bumi Indonesia, 6(2), 228699.

Asih, E. (2023). Wajah Pendidikan Jawa Barat 2023: Antara Tantangan Berat dan Harapan Masa Depan. https://www.pikiran-rakyat.com/pendidikan/pr-017519764/wajah-pendidikan-jawa-barat-2023-antara-tantangan-berat-dan-harapan-masa-depan?page=allDewa,

Awange, J. L., & Kiema, J. (2018). Fundamentals of Remote Sensing. In Environmental science and engineering (p. 115). Springer Nature. https://doi.org/10.1007/978-3-030-03017-9_7

Bere, E., Van der Horst, K., Oenema, A., Prins, R., & Brug, J. (2008). Socio-demographic factors as correlates of active commuting to school in Rotterdam, the Netherlands. Preventive medicine, 47, 412-416. doi:10.1016/j.ypmed.2008.06.019

Ebinum, U. S., Akamagune, N. E., & Ugbong, B. I. (2017). The relationship between school distance and academic achievement of primary school pupils in Ovia North-East LGA, Edo State Nigeria. International Journal of Advanced Research and Publications, 1(5), 427-435.

Ghodousi, M., Sadeghi?Niaraki, A., Rabiee, F., & Choi, S.-M. (2020). Spatial-Temporal Analysis of Point Distribution Pattern of Schools Using Spatial Autocorrelation Indices in Bojnourd City. In Sustainability (Vol. 12, Issue 18, p. 7755). Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/su12187755

Hadibasyir, H. Z., Firdaus, N. S., Aisah, S. N., Pratama, F., & Prasetyo, Y. B. (2023). Remote sensing and GIS integration for analysing spatial distribution of senior and vocational high school education facilities in Klaten Regency, Indonesia. In AIP conference proceedings (Vol. 2795, p. 20015). American Institute of Physics. https://doi.org/10.1063/5.0136916

Irawan (2024). PEMBANGUNAN DI KBB BELUM MERATA. https://jabar.antaranews.com/berita/29238/pembangunan-di-kbb-belum-merata

Kholifatun, U., & Sari, D. N. (2023). Analisis Pola Persebaran Fasilitas Pendidikan Tingkat SMA Sederajat di Kabupaten Grobogan Menggunakan Sistem Informasi Geografis (SIG) (Bachelor's thesis, Universitas Muhammadiyah Surakarta).

Kartika, I. H. D., & Fikriyah, V. N. (2023). Analisis Pola Sebaran Fasilitas Pendidikan Dasar Dengan Pemanfaatan Sistem Informasi Geografi (SIG) Di Kecamatan Klaten Selatan Kabupaten Klaten (Bachelor's thesis, Universitas Muhammadiyah Surakarta).

Kurniawan, M., & Putri, I. M. G. (2023). Analisis Keterjangkauan Dan Pola Sebaran SMA/SMK/MA Negeri Di Kabupaten Tangerang Mengunakan Nearest Neighbor Analysis. Jurnal Analisa Pemikiran Insan Cendikia (Jurnal APIC), 6(1), 74-85.

Mukhlis, M., & Harudu, L. (2019). Pola Persebaran Dan Keterjangkauan Lokasi Sekolah Terhadap Pemukiman Dengan Menggunakan Sistem Informasi Geografi Kecamatan Batauga Kabupaten Buton Selatan. Jurnal Penelitian Pendidikan Geografi, 4(4), 226.

Murad, A. A., Abdulmuakhir, I., & Ammar, A. (2020). Using Geographical Information System for Mapping Public Schools Distribution in Jeddah City. In International Journal of Advanced Computer Science and Applications (Vol. 11, Issue 5). Science and Information Organization. https://doi.org/10.14569/ijacsa.2020.0110513

Nelson, N., Foley, E., O'Gorman, D., Moyna, N., & Woods, C. (2008). Active commuting to school: How far is too far? The international journal of behavioral nutrition and physical activity, 5, 1. doi:10.1186/1479-5868-5-1

Ningsih, R. I. W., Jumadi, J., & Sunariya, M. I. T. (2024). Visualization of hospital distribution for patients COVID-19 in the City of Surabaya using ArcGIS StoryMaps. In AIP conference proceedings (Vol. 2994, p. 20107). American Institute of Physics. https://doi.org/10.1063/5.0182813

Nirwansyah, A. W., Dewi, R. S., & Demirdag, I. (2023). Vulnerability Analysis of School Buildings to Tsunami in the Cilacap Coastal Area. Forum Geografi, 37(2), 117-133.

Pradana, A. N., Djuraidah, A., & Soleh, A. M. (2023). Land Use Change Model-ling Using Logistic Regression, Random Forest and Additive Logistic Regression in Kubu Raya Regency, West Kalimantan. Forum Geografi, 37(2), 149-163.

Sharma, G., & Patil, G. R. (2021). Spatial and social inequities for educational services accessibility - A case study for schools in Greater Mumbai. In Cities (Vol. 122, p. 103543). Elsevier BV. https://doi.org/10.1016/j.cities.2021.103543

Wardana, K., & Jumadi, J. (2024). Land Use Change Analysis and Remote Sensing-Based Spatial Evaluation In Kendal District, Indonesia in 2015 and 2020. In IOP Conference Series Earth and Environmental Science (Vol. 1357, Issue 1, p. 12010). IOP Publishing. https://doi.org/10.1088/1755-1315/1357/1/012010

Wiseka, S. A., & Hisjam, M. Evaluasi Kapasitas dan Jangkauan Pelayanan Fasilitas Pendidikan Sekolah Menengah Pertama dan Madrasah Tsanawiyah di Kota Surakarta. Performa: Media Ilmiah Teknik Industri, 17(1).