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All Journal Jurnal Kajian Ekonomi dan Pembangunan UNP Journal of Statistics and Data Science
Ihsanul Fikri
Universitas Negeri Padang
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences

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Pengaruh Upah, Pertumbuhan Ekonomi, dan Inflasi Terhadap Pengangguran Di Indonesia Ihsanul Fikri; Ali Anis
Jurnal Kajian Ekonomi dan Pembangunan Vol 5, No 1 (2023): Jurnal Kajian Ekonomi dan Pembangunan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jkep.v5i1.14419

Abstract

The purpose of this research is to find out and analyze how wages, economic growth and inflation affect unemployment in Indonesia. The research data was obtained from secondary data, namely data from the Indonesian Central Bureau of Statistics. The dependent variable in this study is unemployment while the independent variables consist of wages, economic growth and inflation. The analysis used in this study is panel data regression analysis by applying the Random Effect Model (REM) method. The results of the study show that wages have a negative and significant effect on unemployment in Indonesia, while economic growth and inflation have a negative and insignificant effect on unemployment in Indonesia.
Comparison of Fuzzy Time Series Markov Chain and Fuzzy Time Series Cheng to Predict Inflation in Indonesia Ihsanul Fikri; Admi Salma; Dodi Vionanda; Zilrahmi
UNP Journal of Statistics and Data Science Vol. 1 No. 4 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol1-iss4/76

Abstract

Inflation is one of the main microeconomic problems which is a very important economic indicator. Unstable inflation has a negative impact on people’s welfare, thus controlling inflation is important thing for a country. Forecasting is needed to monitor future movements in the inflation rate. In this study, the Fuzzy Time Series Markov Chain and fuzzy time series Cheng methods will be compared in forecasting inflation. The advantage of the fuzzy time series method is that it does not have any special assumptions thet must be met. The purpose of this study is to determine the results of forecasting based on the results of the comparison of the two methods. The result of the comparison of the two methods based on the MAPE value is that fuzzy time series Markov Chain has the smallest value of 6,97%. The result of inflation forecasting for the next 5 periods using the fuzzy time series Markov Chain method is 5,42; 5,71; 5,95; 5,82 and 6,10.
Co-Authors Admi Salma Ali Anis Dodi Vionanda Zilrahmi, Zilrahmi