UNLOCKING THE POWER OF BIG DATA: DIGITAL TRANSFORMATION OF PUBLIC POLICY IN DPRD DKI JAKARTA

Authors

  • Ilham Gemiharto Universitas Padjadjaran

DOI:

https://doi.org/10.14421/pjk.v16i2.2631

Keywords:

big data, policy formulation, public policy, government communication

Abstract

This research delves into the prospects and obstacles associated with utilizing large-scale data in developing public policies within the Indonesian context. Integrating big data technology holds promise as a tool for government agencies aiming to refine the public policy formulation process, ultimately providing enhanced services to the populace. Despite its inherent complexity and costliness, incorporating big data offers the government a means to furnish the most up-to-date, precise, and granular information pertinent to developmental issues. For instance, in the agricultural sector, big data can offer an intricate understanding of the diverse requirements of farmers in distinct regions, such as the differentiation between rice varieties sought by farmers in Kalimantan compared to those in Java. Furthermore, the expansive reservoirs of geophysical and meteorological big data hold the capacity to significantly bolster the government's initiatives concerning natural disaster mitigation policies. Nonetheless, the practical integration of big data still needs to be improved by a dearth of comprehensive regulations governing its application. Additionally, the perils of recurrent data breaches in the Indonesian context pose a formidable challenge. This comprehensive analysis concludes that using big data in policy formulation within Indonesia encounters substantial hurdles that threaten to overshadow the potential advantages this technology could offer in enhancing public policy crafting.

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References

Ali, H., & Titah, R. (2021). Do cities use big data? Understanding the nature and antecedents of big data use by municipalities. Government Information Quarterly, 38(4), 101600. https://doi.org/10.1016/j.giq.2021.101600

Arbex, R., & Cunha, C. B. (2020). Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data. Journal of Transport Geography, 85, 102671. https://doi.org/10.1016/j.jtrangeo.2020.102671

Atriana, R., & Hidayat, F. (2017, July 20). Ini Penyimpangan Proyek e-KTP yang Bikin Rugi Negara Rp 2,3 Triliun. Detik.Com, 1–5. https://news.detik.com/berita/d-3567749/ini-penyimpangan-proyek-e-ktp-yang-bikin-rugi-negara-rp-23-triliun

Broeders, D., Schrijvers, E., van der Sloot, B., van Brakel, R., de Hoog, J., & Hirsch Ballin, E. (2017). Big Data and security policies: Towards a framework for regulating the phases of analytics and use of Big Data. Computer Law & Security Review, 33(3), 309–323. https://doi.org/10.1016/j.clsr.2017.03.002

Bungin, B. (2017). Metodologi Penelitian Kualitatif (B. Bungin (ed.); 2nd ed.). PT Rajagrafindo Persada. https://www.rajagrafindo.co.id/produk/metodologi-penelitian-kualitatif-burhan-bungin/

Chen, F., Hou, J., Gu, X., Hou, J., Pan, Q., & Tang, Z. (2022). Research on the temporal and spatial evolution of the public’s response to the mandatory waste separation policy based on big data mining. Sustainable Production and Consumption, 31, 236–248. https://doi.org/10.1016/j.spc.2022.02.013

Cremin, C. J., Dash, S., & Huang, X. (2022). Big data: Historic advances and emerging trends in biomedical research. Current Research in Biotechnology, 4, 138–151. https://doi.org/10.1016/j.crbiot.2022.02.004

Creswell, J. W. (2017). Research Design Pendekatan Kualitatif, Kuantitatif, dan Mixed (S. Z. Qudsy (ed.); 3rd ed.). Pustaka Pelajar. https://opac.perpusnas.go.id/DetailOpac.aspx?id=1213690

Desarkar, A., & Das, A. (2017). Big-Data Analytics, Machine Learning Algorithms and Scalable/Parallel/Distributed Algorithms. In Internet of Things and Big Data Technologies for Next Generation Healthcare (1st ed., pp. 159–197). Springer Publishing Company. https://doi.org/10.1007/978-3-319-49736-5_8

Firdau, M. I. (2018). Pengaruh Pemanfaatan Teknologi Informasi, Kepatuhan Atas Peraturan, dan Kompetensi SDM Terhadap Kualitas LKKL. Indonesian Treasury Review Jurnal Perbendaharaan Keuangan Negara Dan Kebijakan Publik, 3(2), 129–142. https://doi.org/10.33105/itrev.v3i2.69

Gregory, A., & Halff, G. (2020). Big data-driven public relations did the damage. Public Relations Review, 46(2), 101902. https://doi.org/10.1016/j.pubrev.2020.101902

Guenduez, A. A., Mettler, T., & Schedler, K. (2020). Technological frames in public administration: What do public managers think of big data? Government Information Quarterly, 37(1), 101406. https://doi.org/10.1016/j.giq.2019.101406

Hadi, M. Z. (2020). Peluang Implementasi Teknologi Big Data Dan Block Chain Untuk Peningkatan Kinerja Perdagangan Pada Sektor UMKM di Indonesia Pada Era Industri 4.0. Cendekia Niaga, 3(1), 71–80. https://doi.org/10.52391/jcn.v3i1.463

Hakim, D. N., Ramadan, F., & Cahyono, Y. I. (2021). Studi Pemanfaatan Big Data dalam Perumusan Kebijakan Publik pada Sektor Kesehatan. SPECTA Journal of Technology, 5(3), 308–322. https://doi.org/10.35718/specta.v5i3.379

Hergiansa, G. A.-F., Widuri, S. S., & Hadiapurwa, A. (2020). Pemanfaatan Big Data dalam Lingkup Pendidikan. Inovasi Kurikulum, 17(2), 109–116. https://doi.org/10.17509/jik.v17i2.42928

Heryana, D., Setiawati, L., & Suhendar, B. (2020). Sistem Informasi dan Potensi Manfaat Big Data untuk Pendidikan. Gunahumas, 2(2), 350–357. https://doi.org/10.17509/ghm.v2i2.23023

Kandt, J., & Batty, M. (2021). Smart cities, big data, and urban policy: Towards urban analytics for the long run. Cities, 109, 102992. https://doi.org/10.1016/j.cities.2020.102992

Khurshid, M. M., Zakaria, N. H., Rashid, A., Kazmi, R., Shafique, M. N., & Nazir Ahmad, M. (2019). Analyzing diffusion patterns of big open data as policy innovation in the public sector. Computers & Electrical Engineering, 78, 148–161. https://doi.org/10.1016/j.compeleceng.2019.07.010

Kinra, A., Beheshti-Kashi, S., Buch, R., Nielsen, T. A. S., & Pereira, F. (2020). Examining the potential of textual big data analytics for public policy decision-making: A case study with driverless cars in Denmark. Transport Policy, 98, 68–78. https://doi.org/10.1016/j.tranpol.2020.05.026

Kitchin, R., & McArdle, G. (2016). What makes Big Data Big Data? Exploring the ontological characteristics of 26 datasets. Big Data & Society, 3(1), 205395171663113. https://doi.org/10.1177/2053951716631130

Lam, J. C. K., Cheung, L. Y. L., Wang, S., & Li, V. O. K. (2019). Stakeholder concerns of air pollution in Hong Kong and policy implications: A big-data computational text analysis approach. Environmental Science & Policy, 101, 374–382. https://doi.org/10.1016/j.envsci.2019.07.007

Lyu, J., Khan, A., Bibi, S., Chan, J. H., & Qi, X. (2022). Big data in action: An overview of big data studies in tourism and hospitality literature. Journal of Hospitality and Tourism Management, 51, 346–360. https://doi.org/10.1016/j.jhtm.2022.03.014

Maryam, N. S. (2016). Mewujudkan Good Governance Melalui Pelayanan Publik. Jurnal Ilmu Politik Dan Komunikasi, VI(1), 1–18. https://doi.org/https://doi.org/10.34010/jipsi.v6i1.232

Moleong, J. L. (2018). Qualitative Research Methodology (8th ed.). Remaja Rosdakarya. https://opac.perpusnas.go.id/DetailOpac.aspx?id=1133305

Mostafa, N., Ramadan, H. S. M., & Elfarouk, O. (2022). Renewable energy management in smart grids uses big data analytics and machine learning. Machine Learning with Applications, 100363. https://doi.org/10.1016/j.mlwa.2022.100363

Mubaroq, S., & Insyiroh, I. M. (2020). Teknologi Kecerdasan Buatan, Big Data Analysis, dan Internet of Things: Potensi dan Perannya dalam Penanganan Covid-19 di Indonesia. Jurnal Kependudukan Indonesia, 109. https://doi.org/10.14203/jki.v0i0.580

Nainggolan, D. R. M. (2017). Data Science, Big Data, and Predictive Analytics: A Platform for Cyberspace Security Intelligence. Jurnal Pertahanan & Bela Negara, 7(2). https://doi.org/10.33172/jpbh.v7i2.192

Nur, S. K. (2020). Pemanfaatan Big Data Pada Konsep Smart City: Kajian Pustaka. Jurnal INSTEK (Informatika Sains Dan Teknologi), 5(1), 27. https://doi.org/10.24252/instek.v5i1.12140

Pambudi, A. S. (2021). Optimalisasi Pemanfaatan Big Data dalam Evaluasi On Going DAK Fisik Bidang Kesehatan saat Pandemi COVID-19. Bappenas Working Papers, 4(2), 201–217. https://doi.org/10.47266/bwp.v4i2.96

Patgiri, R., & Ahmed, A. (2016). Big Data: The V’s of the Game Changer Paradigm. 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 17–24. https://doi.org/10.1109/HPCC-SmartCity-DSS.2016.0014

Permana, D., Muchsin, S., & Suyeno. (2021). Inovasi Program Pelayanan Publik Berbasis Digital Government (Studi Kasus pada Pengadilan Agama di Kota Malang). Jurnal Respon Publik, 15(1), 32–40. http://riset.unisma.ac.id/index.php/rpp/article/view/10013

Proskuryakova, L. (2022). The interaction of environmental systems and human development in a time of wild cards. A big data-enhanced foresight study. Journal of Environmental Management, 316, 115169. https://doi.org/10.1016/j.jenvman.2022.115169

Putry, R. A. (2022). Dekonstruksi Kebijakan Publik Masa Kini Melalui Eskalasi Kualitas Satu Data Indonesia: Antara Harapan dan Kenyataan. Collaborative Governance and Digital Transformation to The Smart Cities, 23–34. http://repository.unigal.ac.id:8080/handle/123456789/1200

Sirait, E. R. E. (2016). Implementasi Teknologi Big Data di Lembaga Pemerintahan Indonesia. Jurnal Penelitian Pos Dan Informatika, 6(2), 113. https://doi.org/10.17933/jppi.2016.060201

Syafrina, A. E., & Irwansyah. (2018). Privacy Threats in Big Data. Jurnal Penelitian Komunikasi Dan Opini Publik, 22(2). https://doi.org/10.33299/jpkop.22.2.1503

van der Voort, H. G., Klievink, A. J., Arnaboldi, M., & Meijer, A. J. (2019). Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision-making? Government Information Quarterly, 36(1), 27–38. https://doi.org/10.1016/j.giq.2018.10.011

Vydra, S., & Klievink, B. (2019). Techno-optimism and policy-pessimism in the public sector big data debate. Government Information Quarterly, 36(4), 101383. https://doi.org/10.1016/j.giq.2019.05.010

Wanckel, C. (2022). An ounce of prevention is worth a pound of cure – Building capacities for the use of big data algorithm systems (BDAS) in early crisis detection. Government Information Quarterly, 101705. https://doi.org/10.1016/j.giq.2022.101705

Xing, Y., Wang, X., Qiu, C., Li, Y., & He, W. (2022). Research on opinion polarization by big data analytics capabilities in online social networks. Technology in Society, 68, 101902. https://doi.org/10.1016/j.techsoc.2022.101902

Zhao, E., Sun, S., & Wang, S. (2022). New developments in wind energy forecasting with artificial intelligence and big data: A scientometric insight. Data Science and Management. https://doi.org/10.1016/j.dsm.2022.05.002

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Published

2023-12-15

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