Determining the Best Performance Using the Backpropagation Algorithm for Expenditure per Capita in North Sumatra

Authors

  • Yogi Pratama STIKOM Tunas Bangsa
  • Solikhun Solikhun AMIK & STIKOM Tunas Bangsa

DOI:

https://doi.org/10.35335/computational.v11i2.6

Keywords:

Artificial Neural Network, Backpropagation, Per Capita, Performance

Abstract

In an effort to maintain per capita income in Indonesia, the Government must take action through strengthening national protection. Per capita is the average income of all residents in a country. Per capita income is obtained from the distribution of the national income of a country by the total population of that country. There is a decrease in the population per capita of North Sumatra at the Central Statistics Agency (BPS) in 2020. The author will use the backpropagation algorithm to make a performance. Backpropagation iskone ofkmethodkartificial neural networklquite reliablejinlsolvekproblem. In researchj5 models are usedlarchitecture: 4-15-1, 4-30-1,k4-45-1, 4-60-1, 4.-75-1, fromjfive modelslThus, the architectural model 4 -75-1 provides the best accuracy withK452 iteration epochs and MSE is 0.00001536

References

Alliger, G. M., & Janak, E. A. (1989). Kirkpatrick’s levels of training criteria: Thirty years later. Personnel Psychology, 42(2), 331–342.

Anggraeni, W., Mahananto, F., Sari, A. Q., Zaini, Z., & Andri, K. B. (2019). Forecasting the Price of Indonesia’s Rice Using Hybrid Artificial Neural Network and Autoregressive Integrated Moving Average (Hybrid NNs-ARIMAX) with Exogenous Variables. Procedia Computer Science, 161, 677–686.

Bidone, E. D., & Lacerda, L. D. de. (2004). The use of DPSIR framework to evaluate sustainability in coastal areas. Case study: Guanabara Bay basin, Rio de Janeiro, Brazil. Regional Environmental Change, 4(1), 5–16.

Erinç Yeldan, A., & Ünüvar, B. (2016). An assessment of the Turkish economy in the AKP era. Research and Policy on Turkey, 1(1), 11–28.

http://e-jurnal.pnl.ac.id/infomedia/article/view/625

Fields, G. S. (2004). A guide to multisector labor market models.

Govoruschenko, Т. О. (2007). Model of decision maker of repeated application software testing system. Радіоелектронні і Комп’ютерні Системи, 7, 191–198.

Guha, A. B. (1974). Rumania as a development model. Journal of Peace Research, 11(4), 297–323.

GUIDE, B. (n.d.). THE INDONESIAN MARKET.

Hook, W., & Replogle, M. (1996). Motorization and non-motorized transport in Asia: Transport system evolution in China, Japan and Indonesia. Land Use Policy, 13(1), 69–84.

Miller, A., Reandelar, M. J., Fasciglione, K., Roumenova, V., Li, Y., & Otazu, G. H. (2020). Correlation between universal BCG vaccination policy and reduced mortality for COVID-19. MedRxiv.

http://publikasi.dinus.ac.id/index.php/technoc/article/view/1769

http://ejurnal.stmik-budidarma.ac.id/index.php/komik/article/view/941

Susilawati, S., Falefi, R., & Purwoko, A. (2020). Impact of COVID-19’s Pandemic on the Economy of Indonesia. Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences, 3(2), 1147–1156.

Wahyu Azizah, E., & Kusuma, H. (2018). Pengaruh Pendidikan, Pendapatan Perkapita Dan Jumlah Penduduk Terhadap Kemiskinan Di Provinsi Jawa Timur. Jurnal Ilmu Ekonomi, 2, 167–180.

Wardani, S., Solikhun, S., & ... (2019). Jaringan Saraf Tiruan Memprediksi Rata-Rata Pengeluaran Perkapita Untuk Makan dan Bukan Makanan Menurut Provinsi. … Nasional Sains Dan …, 630–635.

Woli, K. P., Nagumo, T., Kuramochi, K., & Hatano, R. (2004). Evaluating river water quality through land use analysis and N budget approaches in livestock farming areas. Science of the Total Environment, 329(1–3), 61–74.

Woo, W. T., & Hong, C. (2010). Indonesia’s economic performance in comparative perspective and a new policy framework for 2049. Bulletin of Indonesian Economic Studies, 46(1), 33–64.

Downloads

Published

2022-08-28

How to Cite

Pratama, Y., & Solikhun, S. (2022). Determining the Best Performance Using the Backpropagation Algorithm for Expenditure per Capita in North Sumatra. International Journal of Mechanical Computational and Manufacturing Research, 11(2), 93–99. https://doi.org/10.35335/computational.v11i2.6