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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Suprayogi, Muhammad Aziz
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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MULTINOMIAL LOGISTIC REGRESSION MODEL USING MAXIMUM LIKELIHOOD APPROACH AND BAYES METHOD ON INDONESIA'S ECONOMIC GROWTH PRE TO POST COVID-19 PANDEMIC Purwanto, Arie; Suprayogi, Muhammad Aziz; Setiawan, Erwan; Loly, Joao Ferreira Rendes Bean; Rahman, Gusti Arviana; Kurnia, Anang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp51-62

Abstract

Economic growth in Indonesia has become a major concern in the global context, especially before and after the Covid-19 pandemic. Key sectors such as tourism, manufacturing, trade and transportation have been seriously affected by restrictions on travel and economic activity imposed to control the spread of the virus. Therefore, it is considered necessary to carry out modeling to describe existing conditions. In this research, two approaches were used, namely the Maximum Likelihood approach and the Bayes approach. The use of methods in general as research material for researchers to study these two methods further. So far the algorithm used for the Bayes concept method is Markov Chain Monte Carlo with Hasting's Metropolis method. The parameter estimation results obtained from both methods are considered quite identical. However, it is necessary to pay attention to the iteration procedure that will be carried out. The selection of factors used in the iteration process is very determining in obtaining estimated parameter values. Furthermore, the results obtained so far do not contain any fundamental differences regarding economic growth in Indonesia. In general, Indonesia can be said to be stable in terms of economic growth.
Co-Authors Anang Kurnia Erwan Setiawan, Erwan Loly, Joao Ferreira Rendes Bean Purwanto, Arie Rahman, Gusti Arviana