Download fulltext HTML
Purwanto, T. A., & Safitri, M. (2018). Analysis of Company Tax Compliance Related to Foreign Investment: Case Study in Indonesia. KnE Social Sciences, 3(11), 1020–1031. https://doi.org/10.18502/kss.v3i11.2826

https://doi.org/10.18502/kss.v3i11.2826

statistics

  • 312 Abstract Views
  • 181 PDF Views
  • 0 HTML Views

authors

  • T A Purwanto
    No author data available.
  • M Safitri
    No author data available.

Published Date

  • Aug 8, 2018

Analysis of Company Tax Compliance Related to Foreign Investment: Case Study in Indonesia

KnE Social Sciences / The 2nd International Conference on Vocational Higher Education (ICVHE) 2017 / Pages 1020–1031

Abstract

This research is an application to realize a system that is capable of providing data and information between levels of economic growth and Indonesian export between 2010 and 2015. Data from the system that was created dug deeper to find out the prediction of drug distribution in the future. The system to be built is the system that is able to predict the level of export needs that will happen in time (month/year) that you want based on the data of the time (month/year) using ANFIS system. The ANFIS system will search the best function to predict the export needs in the year 2010. Furthermore, the output is used as the data in 2010. The data is output as the prediction will be matched with actual data, whether the resulting function of ANFIS system has a small error. If so, then the function obtained is optimal.


 


 


Keywords: time series prediction, neural network, ANFIS

References
[1] Sebastian Galiani, Stephen Knack, Lixin Xu, Ben Zou. The effect of aid on growth: evidence from a Quasi-experiment pp. 1-33, Journal of Economic Growth, 2017, vol. 22, issue 1, 1-33,20


[2] Jens J. Krüger, Revisiting the world technology frontier: a directional distance function approach. Journal of Economic Growth, 2017, vol. 22, issue 1, pages 67-95


[3] Pietro Peretto, Simone Valente, Growth on a finite planet: resources, technology and population in the long run, Growth on a finite planet: resources, technology and population in the long run.


[4] Markus Brueckner, Era Dabla Norris, Mark Gradstein, National income and its distribution, Journal of Economic Growth, 2015, vol. 20, issue 2, 149-175


[5] Jang, J., 1993. SR ANFIS: Adaptive-Network-based fuzzy inference systems, IEEE Trans. On Systems, Man and Cybernetics, 23 (03): 665-685.


[6] Chang, J., SR 1997. Neuro-Fuzzy and Soft Computing. New Jersey Prentice-Hall.


[7] Gorzalczany MB, A. Gluszek. 2000. neuro- fuzzy systems for rule-based modeling of dynamic processes. Proceedings of ESIT, 2000, pp. 416-422.


[8] Arna Fariza. ”Genetic Algorithm Thesis Hybrid Simulated Annealing for time series forecasting” Graduate Program of the Institute of Technology Surabaya, July 2003.


[9] G. Atsalakis, Ucenic ”Time series prediction of water consumption using neurofuzzy (ANFIS) approach”.


[10] Makridakis, S., S. Wheelwright, and McGee VE. 1999. Methods and Applications of Forecasting. The second edition. Jilit one. Jakarta: Binarupa characters.


[11] https://www.bps.go.id