Model Sistem Dinamis: Simulasi Formulasi Kebijakan Publik [Dynamic System Model: Simulation Method in Formulation Public Policy]

Lesmana Rian Andhika
| Abstract views: 988 | views: 1975

Abstract

The Dynamic System Model can be practical decision-making tools that allow testing various scenarios of policy formulation. This study focuses on describe policy formulation in a simulation using Dynamic System Model, the purpose of applying the model is to observe a variety of complex structures and may influence the objectives based on the phenomenon of the identified problem. Furthermore, Dynamic System Model can see changes in policy behavior and allow feedback schemes to provide information flows to design complex policy formulations. This study was conducted with a meta-data-analysis approach, aimed to develop systematic knowledge of certain phenomena through analysis of data processed from selected secondary data. To develop argumentation, this study also refers to several cases of previous research and treated as evidence. The results of this study provide information that in a policy formulation simulation model with a dynamic system used aspects of analysis, planning, and control. These three aspects provide a means for assessing the possible causes of irregularities, resulting variety of possible analyzes of various sources of information, methods, references to determine feedback from all related analyzes in a dynamic system. Thus, provide an early warning about the need for further action, but from these three aspects might have an effect, change and deviation from one part of the system, and often differ from what was intended. For this reason, irregularities provide a signal for additional analysis, whether the policy/strategy has been effectively implemented.

Keywords: simulation, model, dynamic system, policy formulation

Abstrak

Model Sistem Dinamis dapat menjadi alat pendukung pengambilan keputusan praktis yang memungkinkan untuk menguji berbagai skenario formulasi kebijakan. Penelitian ini berfokus untuk menggambarkan Model Sistem Dinamis formulasi kebijakan dalam sebuah simulasi, tujuan dari penerapan model tersebut untuk mengamati berbagai struktur yang kompleks, dan mungkin memengaruhi tujuan berdasarkan fenomena masalah yang teridentifikasi. Selain itu, Model Sistem Dinamis dapat melihat perubahan perilaku kebijakan dan memungkinkan skema umpan balik untuk memberikan arus informasi merancang formulasi kebijakan yang lebih kompleks. Penelitian ini dilakukan dengan pendekatan meta-data-analysis, bertujuan untuk mengembangkan pengetahuan secara sistematis tentang fenomena tertentu melalui analisis data yang diolah dari data sekunder terpilih. Untuk mengembangkan argumentasi penelitian ini juga merujuk kepada beberapa kasus penelitian terdahulu dan diperlakukan sebagai bukti. Hasil penelitian ini memberikan informasi bahwa dalam model simulasi formulasi kebijakan dengan sistem dinamis digunakan aspek analysis, planning, dan control. Ketiga aspek ini menyediakan sarana untuk menilai kemungkinan penyebab penyimpangan, menghasilkan berbagai kemungkinan analisis dari berbagai sumber informasi, metode, referensi untuk menetapkan umpan balik dari semua analisis yang terkait dalam sistem dinamis. Dengan demikian memberikan peringatan dini tentang perlunya tindakan lebih lanjut, namun dari ketiga aspek tersebut mungkin menimbulkan efek, perubahan dan penyimpangan satu bagian dari sistem, dan sering berbeda dari pada yang dimaksudkan. Untuk itu penyimpangan memberikan sinyal untuk analisis tambahan, apakah kebijakan/strategi telah diterapkan secara efektif.

Kata kunci: simulasi, model, sistem dinamis, formulasi kebijakan

Keywords

simulasi; sistem dinamis; formulasi kebijakan; simulation; model; dynamic system; policy formulation

Full Text:

PDF

References

Buku:

Albin, S. (1997). Building a System Dynamics Model Part 1: Conceptualization. Massachusetts: Massachusetts Institute of Technology.

Barlas, Y. (2002). System Dynamics: Systematic feedback medeling for policy analysis. In Y. Barlas (Ed.). System Dynamics (h. 1-68). Abu Dhabi: Encyclopedia of Life Support Systems (EOLSS).

Barnett, E. & Thomas, J. (2009). Methods for the synthesis of qualitative research: A critical review. National Centre for Research Methods Working Papers Series, (EPPI) Centre, Social Science Research Unit, Institute of Education, London.

Bender, K., Keller, S., & Willing, H. (2014). The role of international policy transfer and diffusion for policy change in social protection-A review of the state of the art. International Policy Learning and Policy Change: Scientific Inputs for the Dialogue on Social Protection with Global Partners (h. 1-18). Bonn: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH and Bonn-Rhein-Sieg University of Applied Sciences / International Centre for Sustainable Development (IZNE).

Coyle, R. (1996). System Dynamics Modelling: A practical approach. New York: Springer-Science+Business Media.

Dey, I. (1993). Qualitative data analysis: A user-friendly guide for social scientists. London: Routledge.

Duggan, J. (2016). System Dynamics Modeling with R. Switzerland: Springer International Publishing.

Dunn, W.N. (2016). Public policy analysis (5th ed.). Oxon: Routledge.

Dye, T.R. (2013). Understanding public policy (14th ed.). Upper Saddle River, NJ: Pearson Education.

Hill, M. (2005). The Public policy process (4th ed.). Essex: Pearson Education.

Hoppe, R. (2010). The Governance of problems: Puzzling, powering, participation. Bristol: The Policy Press.

Howlett, M. (2011). Designing public policies: Principles and instruments. Oxon: Routledge.

Kay, A. (2006). The dynamics of public policy: Theory and evidence. Cheltenham: Edward Elgar.

Luenberger, D.G. (1979). Introduction to Dynamic System: Theory, models and applications. New York: John Wiley & Sons.

Lyneis, J.M. (2009). Business policy and strategy, System Dynamics Applications to. In R.A. Meyers (Ed.). Encyclopedia of complexity and systems science (h. 69-92). New York: Springer.

Palm III, W.J. (2014). System Dynamics (3rd ed.). New York, NY: McGraw-Hill.

Paterson, B.L., Thorne, S.E., Canom, C., & Jillings, C. (2001). Meta-study of qualitative health research: A practical guide to meta-analysis and meta-synthesis. Thousand Oaks, CA: SAGE Publication.

Richardson, G.P. (1991). System Dynamics: Simulation for policy analysis from a feedback perspective. In P.A. Fishwick (Ed.). Qualitative simulation modeling and analysis (h. 144-156). New York: Springer-Verlag.

Richardson, G.P. & Pugh, A.L. (1981). Introduction to System Dynamics Modeling with DYNAMO. Massachusetts: The Massachusetts Institute of Technology.

Rowell, D. & Wormley, D. N. (1997). System Dynamics: An introduction. Upper Saddle River, NJ: Prentice-Hall.

Sterman, J.D. (2000). Business Dynamics Systems thinking and modeling for a complex world. Boston: McGraw-Hill Higher Education.

Stewart, J. (2009). Public policy values. Hampshire: Palgrave Macmillan.

Jurnal:

Aghion, P., Algan, Y., Cahuc, P., & Shleifer, A. (2010). Regulation and distrust. The Quarterly Journal of Economics, 125(3), 1015-1049. doi:10.3386/w14648.

Arnold, G. (2014). Policy learning and science policy innovation adoption by street-level bureaucrats. Journal of Public Policy, 34(3), 389-414. doi:10.1017/S0143814X14000154.

Bérard, C., Cloutier, L.M., & Cassivi, L. (2016). The effects of using System Dynamics-based decision support models: Testing policy-makers boundaries in a complex Situation. Journal of Decision Systems, 26(1), 45-63. doi:10.1080/12460125.2016.1204212.

Bovens, M. & Hart, P. (2016). Revisiting the study of policy failures. Journal of European Public Policy, 23(5), 653-666. doi:10.1080/13501763.2015.1127273.

Chen, Y.T., Tu, Y.M., & Jeng, B. (2011). A machine learning approach to policy optimization in System Dynamics Models. Systems Research and Behavioral Science, 28(1), 369-390. doi:10.1002/sres.1089.

Dawes, S.S. (2010). Stewardship and usefulness: Policy principles for information-based transparency. Government Information Quarterly, 27(4), 377-383. doi:10.1016/j.giq.2010.07.001.

Estrada, M.A. & Park, D. (2018). The past, present and future of policy modeling. Journal of Policy Modeling, 40(1), 1-15. doi:10.1016/j.jpolmod.2018.01.003.

Findiastuti, W., Singgih, M.L., & Anityasari, M. (2018). Indonesian sustainable food availability policy assessment using System Dynamics: A solution for complexities. Cogent Food & Agriculture, 4(1455795), 1-21. doi:10.1080/23311932.2018.1455795.

Ghaffarzadegan, N., Lyneis, J., & Richardson, G.P. (2011). How small System Dynamics Models can help the public policy process. System Dynamics Review, 27(1), 22-44. doi:10.1002/sdr.442.

Gilardi, F. (2016). Four ways we can improve policy diffusion research. State Politics & Policy Quarterly, 16(1), 8-21. doi:10.1177/1532440015608761.

Groff, J.S. (2013). Dynamic Systems Modeling in educational system design & policy. New Approaches in Educational Research, 2(2), 72-81. doi:10.7821/naer.2.2.72-81.

Henriksen, L.F. (2013). Economic Models as devices of policy change: Policy paradigms, paradigm shift, and performativity. Regulation & Governance, 7(4), 481-495. doi:10.1111/rego.12031.

Homer, J.B. & Hirsch, G.B. (2006). System Dynamics Modeling for public health: Background and opportunities. American Journal of Public Health, 96(3), 452-458. doi:10.2105/AJPH.2005.062059.

Hoppe, R. (2018). Rules of thumb for problem structuring policy design. Policy Design and Practice, 1(1), 12-29. doi:10.1080/25741292.2018.1427419.

Howlett, M. (2012). The Lessons of failure: Learning and blame avoidance in public policy-making. International Political Science Review, 33(5), 539-555. doi:10.1177/0192512112453603.

Kunc, M., Morecroft, J.D., & Brailsford, S. (2018). Special issue on advances in system dynamics modelling from the perspective of other simulation methods. Journal of Simulation, 12(2), 87-89. doi:10.1080/17477778.2018.1469385.

Liu, X., Lindquist, E., Vedlitz, A., & Vincent, K. (2010). Understanding local policymaking: Policy elites’ perceptions of local agenda setting and alternative policy selection. The Policy Studies Journal, 38(1), 69-91. doi:10.1111/j.1541-0072.2009.00345.x.

Loftis, M.W. & Mortensen, P.B. (2017). A Dynamic Linear Modelling approach to public policy change. Journal of Public Policy, 1-27. doi:10.1017/S0143814X17000186.

Maggetti, M. & Gilardi, F. (2015). Problems (and solutions) in the measurement of policy diffusion mechanisms. Journal of Public Policy, 00(0), 1-21. doi:10.1017/S0143814X1400035X.

Mortensen, P.B. (2010). Political attention and public policy: A study of how agenda setting matters. Scandinavian Political Studies, 33(4), 256-380. doi:10.1111/j.1467-9477.2010.00254.x.

Navarra, D. & Bianchi, C. (2013). Territorial governance, e-government and sustainable development policy: A System Dynamics Approach. 12th International Conference on Electronic Government (EGOV), pp. 14-25.

Rashedi, R. & Hegazy, T. (2015). Strategic policy analysis for infrastructure rehabilitation using System Dynamics. Structure and Infrastructure Engineering, 12(6), 667-681. doi:10.1080/15732479.2015.1038723.

Sayyadi, R. & Awasthi, A. (2016). A System Dynamics based simulation model to evaluate regulatory policies for sustainable transportation planning. International Journal of Modelling and Simulation, 37(1), 25-35. doi:10.1080/02286203.2016.1219806.

Trailer, J.W. & Garsson, K. (2005). A System Dynamics Approach to assessing public policy impact on the sustainable growth rate of new ventures. New England Journal of Entrepreneurship, 8(1), 1-14.

Trochim, W.M. (2009). Evaluation policy and evaluation practice. New Directions for Evaluation, 123(1), 13-32. doi:10.1002/ev.303.

Uriona, M. & Grobbelaar, S.S. (2018). Innovation system policy analysis through System Dynamics Modelling: A systematic review. Science and Public Policy, 46(1), 28-44. doi:10.1093/scipol/scy034.

Vrat, L.U. (2018). Policy boomerang in technical education: A System Dynamics perspective. Journal of Advances in Management Research, 14(2), 1-33. doi:10.1108/JAMR-08-2016-0065.

Wheat, I.D. (2010). What can System Dynamics learn from the public policy implementation literature? Systems Research and Behavioral Science, 27(1), 425-442. doi:10.1002/sres.1039.

Workman, S., Jones, B.D., & Jochim, A.E. (2009). Information processing and policy dynamics. The Policy Studies Journal, 37(1), 75-92.

Sumber Digital:

Kemendagri. (2016). Unggah 3.143 Perda, Mendagri berterimakasih ke semua pihak. Diperoleh tanggal 21 Juni 2018, dari http://www.kemendagri.go.id/news/2016/06 /21/unggah-3143-perda-mendagri-berterimakasih-ke-semua-pihak.

Peraturan:

Peraturan Presiden Republik Indonesia No. 104 tahun 2007 tentang Penyediaan, Pendistribusian, dan Penetapan Harga Liquefied Petroleum Gas (LPG) Tabung 3 Kilogram.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Refbacks

  • There are currently no refbacks.