Deep learning applied to the strategic planning of the regional governments of the central macro region to determine the alignment with the policies of the central government; [Deep learning aplicado ao planejamento estratégico dos governos regionais da macrorregião central para determinar o alinhamento com as políticas do governo central]

Mercado Rivas R.Y.; Cerrón Pérez J.L.; Raraz Tupac Yupanqui O.C. · Sapienza (2022) · DOI: 10.51798/sijis.v3i4.436

Resumen

The strategic planning of the regional governments of the central macro region seems to operate independently from central government policies, showing a clear lack of alignment with respect to the continuous improvement of the education and health sectors, because although the national decrees dictate concrete objectives as achievement indicators, in practice these are not being achieved. In this research work, a documentary analysis of central government policies and strategic planning of the central macro region is developed, with a special focus on the health, education and other sectors, so that through the use of Deep Learning tools it is possible to determine the alignment of each of the regions to national policies. As a result, it was possible to create a model that can classify text through a short-term memory network (LSTM), which determined in percentage terms how many of the regional institutional strategic objectives are aligned to those established by the sectors of national scope such as health, education and others. On average, a value of 78.08 % coincidence was obtained for the total number of regional institutional strategic objectives aligned with those of the central government.

Instituciones: Universidad Nacional del Centro del Perú