Subsídio às Fiscalizações Públicas: Identificação dos Municípios com gastos discrepantes na Educação Básica
DOI:
https://doi.org/10.55532/1806-8944.2022.158Palavras-chave:
Clusterização de municípios, Detecção de anomalias, Despesas públicas, Educação BásicaResumo
Os gastos públicos devem ser constantemente monitorados pelos órgãos governamentais. Neste contexto, torna-se primordial a aplicação de tecnologia para a produção de informações estratégicas que apoiem ações de combate à corrupção e à má gestão dos recursos públicos. Com a disponibilização do Sistema de Informações sobre Orçamentos Públicos em Educação (SIOPE), o presente trabalho emprega técnicas de mineração de dados para a detecção de despesas atípicas no Ensino Fundamental, realizadas pelos municípios em 2018 – que podem constituir eventos ocasionais (como obras em escolas) ou representar indícios de irregularidades. Aplicou-se clusterização de municípios e algoritmos de detecção de anomalias em um grupo de municípios semelhantes. Os resultados alcançados (se o município é anômalo e seu grau de anomalia) podem ser agregados ao planejamento das ações de controle e, ainda, subsidiar a adoção de providências cabíveis por parte de demais instâncias, como o Ministério da Educação e conselhos de controle social.
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BRAZIL, National Institute for Educational Studies and Research Anísio Teixeira. Transition Rates 2014/2015. Available at: <http://portal.inep.gov.br/web/guest/indicadores-educacionais>. Accessed 12 Oct 2019f.
BRAZIL, National Institute of Educational Studies and Research Anísio Teixeira. Statistical Notes - Census of Basic Education 2019. Available at: <http://portal.inep.gov.br/censo-escolar>. Accessed on 02 Feb 2020.
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ARCOVERDE, Léo, TOLEDO, Luiz Fernando. CGU points out irregular use of almost R$ 51 million from Fundeb throughout the country. G1 News Portal, 2019. Available at: <https://g1.globo.com/educacao/noticia/2019/08/15/cgu-aponta-uso-irregular-de-quase-r-51-milhoes-do-fundeb-em-todo-o-pais.ghtml>. Accessed 20 Nov 2019.
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Comptroller's Office launches tool for preventive and automated evaluation of tender notices. Federal Government, 2015. Available at: <https://www.gov.br/cgu/pt-br/assuntos/noticias/2015/06/controladoria-lanca-ferramenta-para-avaliacao-preventiva-e-automatizada-de-editais-de-licitacao>. Accessed on 18 feb 2020
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PROVOST, Foster; FAWCETT, Tom. Data Science for Business. What you need to know about data mining and data analytical thinking. 1.ed. Rio de Janeiro: Alta Books, 2016. ISBN: 9788576089728.
BRAZIL. 1988 Constitution of the Federative Republic of Brazil. Brasília, 1988.
Available at:
<http://www.planalto.gov.br/ccivil_03/constituicao/constituicaocompilado.htm>. Accessed 19 Nov 2019.
BRAZIL. Law no. 9.394, of December 20, 1996. Establishes the guidelines and bases of national education. Brasília, 1996. Available at: <http://www.planalto.gov.br/ccivil_03/leis/L9394compilado.htm>. Accessed on: 19 Nov 2019.
BRAZIL. Law no. 11.494, of June 20, 2007. Regulates the Fund for Maintenance and Development of Basic Education and Valorization of Education Professionals - FUNDEB. Brasília, 2007. Available at: <http://www.planalto.gov.br/ccivil_03/_ato2007-2010/2007/lei/l11494.htm>. Accessed on: 19 Nov 2019.
BRAZIL, Comptroller General of the Union. Inspection Report No. 201602219 - Fund for Maintenance and Development of Basic Education and Valorization of Education Professionals (Fundeb). Available at <https://auditoria.cgu.gov.br/download/12682.pdf>. Accessed on: 19 Nov 2019a.
BRAZIL, Comptroller General of the Union. Inspection Report No. 201602218 - Fund for Maintenance and Development of Basic Education and Valorization of Education Professionals (Fundeb). Available at <https://auditoria.cgu.gov.br/download/12685.pdf>. Accessed on: 19 Nov 2019b.
BRAZIL, Comptroller General of the Union. Annual Audit Report No. 201900673 - National Fund for the Development of Education - Fiscal Year 2018. Available at: <https://auditoria.cgu.gov.br/download/13670.pdf>. Accessed 20 Dec 2019c.
BRAZIL, Comptroller General of the Union. Guidelines for monitoring the actions of the Fund for Maintenance and Development of Basic Education and for Valuing Education Professionals (FUNDEB). Available at <https://www.cgu.gov.br/Publicacoes/controle-social/arquivos/fundeb2012.pdf>. Accessed on: 20 Dec 2019d.
BRAZIL, Office of the Comptroller General. Understand the indicators (Vulnerability Matrix). Available at: <https://www.cgu.gov.br/assuntos/auditoria-e-fiscalizacao/programa-de-fiscalizacao-em-entes-federativos/1-ciclo/1o-ciclo/entenda-os-indicadores>. Accessed 21 Dec 2019e.
BRAZIL, Office of the Comptroller General. Inspection Report No. 201902570 - Mata Roma (MA) - Education and Health. Available at <https://auditoria.cgu.gov.br/download/13842.pdf>. Accessed on: 20 Jan 2020a.
BRAZIL, Comptroller General of the Union. Ordinance No. 3,553, of November 12, 2019. Approves the Internal Regulations and the Demonstrative Chart of Commissioned Positions and Functions of Trust of the Office of the Comptroller General of the Union - CGU and makes other provisions. Available at <http://www.in.gov.br/web/dou/-/portaria-n-3.553-de-12-de-novembro-de-2019-227654932>. Accessed on 02 Feb 2020b.
BRAZIL, National Fund for Education Development. SIOPE Portal: Information System on Public Budgets in Education. Available at: <https://www.fnde.gov.br/fnde_sistemas/siope>. Accessed 06 Aug 2019.
BRAZIL, Brazilian Institute of Geography and Statistics. Population Estimates. Available at: <https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativas-de-populacao.html?=&t=resultados>. Accessed 08 Oct 2019.
BRAZIL, Anísio Teixeira National Institute for Educational Studies and Research. IDEB Results. Available at: <http://portal.inep.gov.br/web/guest/educacao-basica/ideb/resultados>. Accessed 08 Oct 2019a.
BRAZIL, Anísio Teixeira National Institute for Educational Studies and Research. IDEB Results. Municipalities - Regular Elementary School - Early Years.
Available at: <http://download.inep.gov.br/educacao_basica/portal_ideb/planilhas_para_download/2017/ disclosure_initial_years_municipalities2017-updated-Jun_2019.xlsx>. Accessed 08 Oct 2019b.
BRAZIL, Anísio Teixeira National Institute for Educational Studies and Research. IDEB Results. Municipalities - Regular Elementary School - Final Years.
Available from: <http://download.inep.gov.br/educacao_basica/portal_ideb/planilhas_para_download/2017/divulgacao_anos_finais_municipios2017-atualizado-Jun_2019.xlsx>. Accessed 08 Oct 2019c.
BRAZIL, Anísio Teixeira National Institute for Educational Studies and Research. IDEB Results. Municipalities - High School. Available at: <http://download.inep.gov.br/educacao_basica/portal_ideb/planilhas_para_download/2017/divulgacao_ensino_medio_municipios2017-atualizado-Jun_2019.xlsx>. Accessed 08 Oct 2019d.
BRAZIL, National Institute of Educational Studies and Research Anísio Teixeira. Instructions for using the Microdata of the 2018 Basic Education Census. Available at: <http://download.inep.gov.br/microdados/microdados_educacao_basica_2018.zip>. Accessed 12 Oct 2019e.
BRAZIL, National Institute for Educational Studies and Research Anísio Teixeira. Transition Rates 2014/2015. Available at: <http://portal.inep.gov.br/web/guest/indicadores-educacionais>. Accessed 12 Oct 2019f.
BRAZIL, National Institute of Educational Studies and Research Anísio Teixeira. Statistical Notes - Census of Basic Education 2019. Available at: <http://portal.inep.gov.br/censo-escolar>. Accessed on 02 Feb 2020.
BRAZIL, Ministry of Education. SIOPE Municipal 2018: User Guidelines Manual. Available at: https://www.fnde.gov.br/index.php/centrais-de-conteudos/publicacoes/category/139-siope?download=11869:manual-siope-municipal. Accessed 06 Aug. 2019.
BRAZIL, Ministry of Planning, Development and Management. Ordinance #42, of April 14, 1999. Updates the breakdown of spending by functions and makes other provisions. Available at <http://www.orcamentofederal.gov.br/orcamentos-anuais/orcamento-1999/Portaria_Ministerial_42_de_140499.pdf>. Accessed on 02 feb 2020.
Ministry of Planning, Development and Management. Federal Budget Secretariat. Technical manual of budget - MTO 2017. Brasília, 2016. Available at: <http://www.orcamentofederal.gov.br/informacoes-orcamentarias/manual-tecnico/mto_2017-1a-edicao-versao-de-06-07-16.pdf>. Accessed on 02 Feb 2020.
BRAZIL: United Nations Development Programme. What is HDI. Available at: <https://www.br.undp.org/content/brazil/pt/home/idh0/conceitos/o-que-e-o-idhm.html>. Accessed 13 Oct 2019.
BRAZIL. Federal Court of Accounts. Judgment No. 618/2014. Plenary. Rapporteur: Minister Valmir Campelo. Session of 3/19/2014. Available at: <https://pesquisa.apps.tcu.gov.br/#/redireciona/acordao-completo/%22ACORDAO-COMPLETO-1300927%22>. Accessed on: 02 Feb 2020.
CHAPMAN, Pete et al. CRISP-DM 1.0: Step-by-step data mining guide. Technical report.
The CRISP-DM consortium, 2000. Available at: <https://pdfs.semanticscholar.org/5406/1a4aa0cb241a726f54d0569efae1c13aab3a.pdf>. Accessed on: 29 Jan 2020.
GOLDSTEIN, Markus and UCHIDA, Selichi. A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data. PLoS ONE, 11(4): e0152173, April, 2016. Available at: <https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152173>
Accessed 23 Dec 2019.
GOIX, Nicolas. How to Evaluate the Quality of Unsupervised Anomaly Detection Algorithms? 2016. Available at: <https://arxiv.org/abs/1607.01152> Accessed on: 25/02/2020.
HE, Zengyou; XIAOFEI, Xu and SHENGCHUN, Deng. Discovering cluster-based local outliers. Pattern Recognit. Lett., vol. 24, pp. 1641-1650, 2003.
IBM. IBM SPSS Modeler CRISP-DM Guide. Available at: <https://www.ibm.com/support/knowledgecenter/SS3RA7_18.2.1/modeler_crispdm_ddita/clementine/crisp_help/crisp_overview.html>, 2019. Accessed 29 Jan 2020.
KRIEGEL, Hans-Peter, SCHUBERT, Matthias, and ZIMEK, Arthur. Angle-based outlier detection in high-dimensional data. In Proceedings of the 14th ACMKDD International Conference on Knowledge Discovery and Data Mining (pp. 444-452). Association for Computing Machinery. Las Vegas, NV, 2008.
LEEK, Jeff. The Elements of Data Analytic Style. Leanpub, Victoria British Columbia, 2015.
PEDREGOSA, Fabian et all. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 2011. volume 12, p. 2825-2830.
PROJECT JUPYTER. Project Jupyter®. Available at: <https://jupyter.org>. Accessed 30 Aug 2019.
PYTHON, Software Foundation. Python. Available at: <https://www.python.org/>. Accessed 30 Aug 2019.
QUEIROZ, Christina. FAPESP Research: Complex Gears. Fed by tax revenue, education funding schemes such as Fundeb, which expires in 2020, pose a challenge to the federal government. Available at: https://revistapesquisa.fapesp.br/2019/03/12/engrenagem-complexa>. Accessed on 02 Feb 2020.
SEABORN. SEABORN statistical data visualization. Available at <https://seaborn.pydata.org/index.html>. Accessed 30 Aug 2019.
SEN, Soumya. Intercluster and Intracluster Distance. Available at: <https://www.geeksforgeeks.org/ml-intercluster-and-intracluster-distance>. Accessed 20 Dec 2019.
SRIVASTAVA, Shobhit. Feature Scaling in Scikit-learn. Available at: <https://medium.com/analytics-vidhya/feature-scaling-in-scikit-learn-b11209d949e7>
Accessed 20 Dec 2019.
THE PANDAS PROJECT. Pandas - Python Data Analysis Library. Available at: <https://pandas.pydata.org>. Accessed 30 Aug 2019.
THESING, Ana Paula. Analytics and Big Data are powerful weapons against corruption. 2019. Available at: <https://www.itforum365.com.br/analytics-e-big-data-sao-poderosas-armas-contra-a-corrupcao>. Accessed on 20 Feb 2020.
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Machado, R. G. (2022). Subsídio às Fiscalizações Públicas: Identificação dos Municípios com gastos discrepantes na Educação Básica. CADERNOS DE FINANÇAS PÚBLICAS , 22(01). https://doi.org/10.55532/1806-8944.2022.158
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