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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) EKONOMIS : Journal of Economics and Business
Erianti, Efita
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology

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ANALISIS PENGENDALIAN KUALITAS STATISTIK GULA RAFINASI DENGAN PETA KENDALI MULTIVARIAT T-SQUARE (STUDI KASUS: PT. MAKASSAR TENE) Kasse, Irwan; Erianti, Efita; Irwan, Muh.
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 8 No 1 (2020): Volume 8 Nomor 1
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v8i1.19364

Abstract

Sugar is a simple carbohydrate that is a source of energy. Sugar consumption in each country are different from Indonesia. Demand for sugar in Indonesia is always changing and increasing along with increasing of the population in Indonesia. If sugar consumption in Indonesia is Increasing, Sugar Production have to be increased. Of course, the company have to guarantee the quality of sugar. There are several factors that affect the quality of sugar. So, the company must always check the quality of sugar to be producted by considering these factors. Therefore, this research used multivariate T2 control chart method. This study aims to determine whether refined sugar products have been statistically controlled using multivariate T-Square control chart. The method used is the Statistical Quality Control method with multivariate T-Square control chart. The results of the study show that all refined sugar products have been statistically controlled by using multivariate T-Square control chart after making several revisions and can be a reference in the analysis control chart.
Pemodelan ARIMA-GARCH dalam Peramalan Kurs Rupiah Terhadap Yen dengan Masalah Keheterogenan Ragam Meilania, Gusti Tasya; Septiani, Adeline Vinda; Erianti, Efita; Notodiputro, Khairil Anwar; Angraini, Yeni
Ekonomis: Journal of Economics and Business Vol 8, No 1 (2024): Maret
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/ekonomis.v8i1.1294

Abstract

The currency exchange rate is the price of a country's currency expressed into another country's currency. At the beginning of 2020, the COVID-19 pandemic affected the weakening and changes in the Rupiah exchange rate against hard currencies, one of which was the Japanese Yen. This affects the expectations of LCS cooperation between Indonesia and Japan in terms of increasing the value of trade to investment between the two countries. Therefore, forecasting the upcoming currency exchange rate is indispensable to determine the upcoming macroeconomic policy. ARIMA is a commonly used quantitative method to forecast future data using past data patterns. The weakness of this method arises when the data violates the assumption of homogeneity of variety that often occurs in financial data, one of which is currency exchange rate data. The ARCH/GARCH model is an effective model for data with uncertain diversity characteristics. However, there is potential to combine ARIMA and ARCH/GARCH into an ARIMA-ARCH/GARCH hybrid model to obtain forecasting results with greater accuracy. In this study, the minimum return data on the Indonesian Rupiah (IDR) exchange rate against the Japanese Yen (JPY) shows the results that the ARIMA(0,0,1) model provides RMSE accuracy of 0.008. While the best forecasting model that can be used to forecast the maximum return data of the IDR exchange rate against JPY is ARIMA(1,0,0)-GARCH(1,1) with a small RMSE accuracy of 0.014. The forecasting results for the minimum return data for buying and selling are expected to strengthen the exchange rate. Meanwhile, the forecasting results for the maximum return data for buying and selling are expected to experience exchange rate weakening.
Co-Authors Angraini, Yeni Irwan Kasse Irwan, Muh. Meilania, Gusti Tasya Septiani, Adeline Vinda