Transformasi Penggunaan Lahan dan Dampak Sosial Budaya Proyek Reklamasi di Tanjungpinang Kota

  • Muhammad Dhahlan Kantor Wilayah BPN Provinsi Kepulauan Riau, Indonesia
  • Ramadhani Naufal Na’afi Sekolah Tinggi Pertanahan Nasional, Yogyakarta, Indonesia
  • Yosia Putra Nababan Sekolah Tinggi Pertanahan Nasional, Yogyakarta, Indonesia
Keywords: Pelantar Settlement, Landuse Change, Reclamation

Abstract

Indonesia, an archipelago with abundant agricultural and marine resources, is witnessing land-use changes due to socio-economic shifts, population increase, and development pressures, notably in coastal areas like Tanjungpinang Kota District. This district's stilt house settlements or fishermen's dwellings must cohabit with the Gurindam 12 (G12) reclamation project, which may influence their development. This study will examine how the G12 reclamation project affected land-use changes and stilt house settlement sustainability. A descriptive quantitative approach using Cellular Automata and Artificial Neural Networks (CA-ANN) predicted land use in 2038. A buffer analysis assessed residential areas' extreme wave disaster risk. The results show significant land-use changes between 2014 and 2023, particularly surrounding stilt houses. Ca-ANN study shows that the G12 reclamation project is affecting settlement patterns, especially in high-risk coastal locations. This study found that the CA-ANN approach accurately identifies land-use change trends and assesses reclamation efforts.

Indonesia sebagai negara kepulauan dengan kekayaan alam dan wilayah perairan yang diakui dunia menghadapi perubahan penggunaan lahan yang dipicu oleh transformasi sosial-ekonomi, pertumbuhan penduduk, serta tekanan pembangunan, terutama di wilayah pesisir seperti Kecamatan Tanjungpinang Kota. Permukiman di atas air laut (pelantar) ini harus beradaptasi dengan proyek reklamasi Gurindam 12 (G12) yang dilaksanakan oleh pemerintah, yang kemungkinan besar mempengaruhi perkembangan permukiman pelantar tersebut. Penelitian ini bertujuan menganalisis dampak proyek reklamasi G12 terhadap perubahan penggunaan lahan dan keberlanjutan permukiman pelantar. Peneliti menggunakan metode deskriptif kuantitatif dengan mengintegrasikan Cellular Automata dan Artificial Neural Networks (CA-ANN) untuk memprediksi penggunaan lahan hingga tahun 2038 serta menganalisis kerentanan permukiman pelantar terhadap risiko bencana gelombang ekstrem menggunakan buffer analysis. Hasil penelitian menunjukkan bahwa periode 2014-2023 terjadi perubahan penggunaan lahan yang berdampak pada kebijakan pengelolaan pesisir dan perencanaan pembangunan berkelanjutan, terutama kehidupan sosial budaya masyarakat pelantar. Analisis menggunakan metode CA-ANN memperkuat temuan ini dan menunjukkan bahwa proyek reklamasi G12 mempengaruhi pola permukiman masyarakat, terutama di daerah pesisir yang berisiko tinggi. Penelitian ini menyimpulkan bahwa metode CA-ANN efektif dalam mengidentifikasi pola perubahan lahan dan memberikan gambaran akurat mengenai dampak faktor-faktor seperti proyek reklamasi.

References

Alcaras, E., & Parente, C. (2023). The Effectiveness of Pan-Sharpening Algorithms on Different Land Cover Types in GeoEye-1 Satellite Images. Journal of Imaging, 9(5), 1-21. https://doi.org/10.3390/jimaging9050093

Dahlia, S., Adiputra, A., Alwin, Najiyullah, M. A., Kamzia, & Rahmadiansyah, F. K. (2020). Analisis Perubahan Penggunaan Lahan Pasca Kejadian Tsunami Tahun 2018 Sebagai Rekomendasi Tata Ruang di Pesisir Pantai Kecamatan Panimbang, Pandeglang, Banten. Jurnal Geografi, Edukasi Dan Lingkungan (JGEL), 4(1), 8-16. https://doi.org/10.29405/jgel.v4i1.3640

Hapsary, M. S. A., Subiyanto, S., & Firdaus, H. S. (2021). Analisis Prediksi Perubahan Penggunaan Lahan Dengan Pendekatan Artificial Neural Network Dan Regresi Logistik Di Kota Balikpapan. Jurnal Geodesi Undip, 10(2), 88-97. https://doi.org/10.14710/jgundip.2021.30637

Heikinheimo, V., Tenkanen, H., Bergroth, C., Järv, O., Hiippala, T., & Toivonen, T. (2020). Understanding the use of urban green spaces from user-generated geographic information. Landscape and Urban Planning, 201, 1-15. https://doi.org/10.1016/j.landurbplan.2020.103845

Ikhwan, Z., Harahap, R. H., Andayani, L. S., & ... (2021). The Economic Potential Of Waste Management In Penyengat Island Tourism, Tanjungpinang City, Riau Island Province, Indonesia. PalArch’s Journal of Archaeology of Egypt / Egyptology, 18(4), 3043-3065. https://archives.palarch.nl/index.php/jae/article/view/6763

Lestari, F. (2022). Environmental management strategy for coastal waters through a dynamic system approach in Tanjungpinang City region, Riau Islands, Indonesia. Akuatikisle: Jurnal Akuakultur, Pesisir Dan Pulau-Pulau Kecil, 6(2), 141-147. https://doi.org/10.29239/j.akuatikisle.6.2.141-147

Mari, T. S., Liew, J., & Ng, V. (2023). Re-establishing traditional stilt structures in contemporary architecture–The possibilities. Archnet-IJAR: International Journal of Architectural Research, 17(1), 88-108. https://doi.org/10.1108/ARCH-12-2021-0353

Mariati. (2021). The Visual City Branding of Tanjungpinang City – Riau Islands. Proceedings of the 1st International Conference on Folklore, Language, Education and Exhibition (ICOFLEX 2019), 512, 83-89 https://doi.org/10.2991/assehr.k.201230.017

Purnamasari, N., Evelin, J., Riyadi, A., Safitri, A., & Niko, N. (2023). Women’s Empowerment Strategy in Building MSMEs in Tanjungpinang City, Riau Islands. Formosa Journal of Applied Sciences, 2(9), 2213–2224. https://doi.org/10.55927/fjas.v2i9.6003

Harianti, W. P., & Nandi, N. (2019). Level of Slum Settlements in Tanjungpinang City, Riau Island. KnE Social Sciences. 3(21), 862–872. https://doi.org/10.18502/kss.v3i21.5017

Ruslan, R., Siska, S., & Surya, B. (2021). Dampak Konversi Lahan Pertanian. Journal of Urban Planning Studies, 1(3), 1-15. https://doi.org/10.35965/jups.v1i3.78

Ullah, H., Hameed, A. A., Rizvi, S. S., Jamil, A., & Kwon, S. J. (2022). Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care. Computational Intelligence and Neuroscience, 2022., 1-8 https://doi.org/10.1155/2022/2532580

Valenzuela, V. P. B., Esteban, M., & Onuki, M. (2020). Perception of Disasters and Land Reclamation in an Informal Settlement on Reclaimed Land: Case of the BASECO Compound, Manila, the Philippines. International Journal of Disaster Risk Science, 11(5), 1-9. https://doi.org/10.1007/s13753-020-00300-y

Wayan, I., Kawakibi, T., Politeknik, P., Batam, P., & Augustinus, D. C. (2017). Analisis Faktor Hospitality Masyarakat Terhadap Wisatawan di Kawasan Wisata Pulau Penyengat Kota Tanjung Pinang Propinsi Kepulauan Riau. Journal of Accounting & Management Innovation, 1(1),38-48. https://doi.org/10.19166/%25JAMI%256%252%252022%25

Xu, T., Gao, J., & Coco, G. (2019). Simulation of urban expansion via integrating artificial neural network with Markov chain–cellular automata. International Journal of Geographical Information Science, 33(10), 1-12. https://doi.org/10.1080/13658816.2019.1600701

Yatoo, S. A., Sahu, P., Kalubarme, M. H., & Kansara, B. B. (2022). Monitoring land use changes and its future prospects using cellular automata simulation and artificial neural network for Ahmedabad city, India. GeoJournal, 87(2), 1-20. https://doi.org/10.1007/s10708-020-10274-5

Zhai, Y., Yao, Y., Guan, Q., Liang, X., Li, X., Pan, Y., Yue, H., Yuan, Z., & Zhou, J. (2020). Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata. International Journal of Geographical Information Science, 34(7), 1-10. https://doi.org/10.1080/13658816.2020.1711915

CROSSMARK
Published
2024-10-31
DIMENSIONS
How to Cite
Dhahlan, M., Na’afi, R. N., & Nababan, Y. P. (2024). Transformasi Penggunaan Lahan dan Dampak Sosial Budaya Proyek Reklamasi di Tanjungpinang Kota. Widya Bhumi, 4(2), 176–191. https://doi.org/10.31292/wb.v4i2.111
Section
Articles