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All Journal Jurnal Sains dan Seni ITS Jurnal Matematika Sains dan Teknologi BENTANG : Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil JMM (Jurnal Masyarakat Mandiri) EIGEN MATHEMATICS JOURNAL Variance : Journal of Statistics and Its Applications Specta Journal of Technology Jurnal Pengabdian UNDIKMA Buletin Statistika dan Aplikasi Terkini JOMPA ABDI: Jurnal Pengabdian Masyarakat Jurnal Statistika dan Komputasi (STATKOM) PIKAT JPNM : Jurnal Pustaka Nusantara Multidisiplin Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Equiva International Journal of Computing Science and Applied Mathematics-IJCSAM
Mega Silfiani
Institut Teknologi Kalimantan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Transportation Other

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Journal : EIGEN MATHEMATICS JOURNAL

 1 
Analisis Dampak COVID 19 terhadap PDRB Provinsi Bali dengan Model Intervensi Mega Silfiani; Farida Nur Hayati; Surya Puspita Sari; Agung Prabowo
Eigen Mathematics Journal Vol. 5 No. 2 Desember 2022
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v5i2.141

Abstract

COVID 19 is a disease caused by SARS-CoV-2. This virus spread very quickly to almost all countries including Indonesia. Bali tourism has developed in such a way and contributed greatly to regional development directly or indirectly. Gross Regional Domestic Product or GRDP has an important role in increasing the economic growth of a region, where the higher the GRDP, it can be said that the economic growth is also high. This study aims to analyze the impact of COVID 19 on the GRDP of the Province of Bali using an intervention model. The data used in this study is secondary data from quarterly GRDP on the basis of current prices in the accommodation, food and drink sector. Data was collected from the first quarter of 2010 to the fourth quarter of 2021. Based on the modeling that has been carried out with the intervention model, the best model to predict the impact of COVID 19 on GRDP in Bali Province is ARIMA(0,1,0)(1,0,0)4 r=1 with SMAPE value of 8.327 and MdAPE of 0.067.
Comparison of Several Univariate Time Series Methods for Inflation Rate Forecasting Salfina, Salfina; Hernanda, Yunissa; Silfiani, Mega
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.200

Abstract

Forecasting inflation is very crucial for a country because inflation is one of indicator to measure development of the country. This study aims to evaluate the effectiveness of three univariate time series methods i.e., ARIMA (Autoregressive Integrated Moving Average), Double Exponential Smoothing (DES), and Trend Projection (TP), in forecasting Indonesia’s monthly inflation rates using data from 2018 to 2022. The analysis identifies DES as the most accurate method, evidenced by its lowest Root Mean Square Error (RMSE) value of 2.9296, outperforming ARIMA and TP, which have RMSE values of 13.1479 and 3.47053, respectively. Consequently, DES was selected as the preferred model for forecasting inflation over the next 36 month, with the forecasts indicating a consistent downward trend in inflation throughout the year. While these findings highlight DES's effectiveness, the study also acknowledges limitations, including its reliance on univariate models that do not incorporate other economic variables, and the potential limitations of the dataset’s specific time frame. To address these limitations, future research should consider multivariate models, integrate machine learning techniques, and conduct scenario analyses to improve forecast accuracy and robustness. Despite these constraints, the study provides valuable insights into inflation forecasting in Indonesia, offering a practical tool for policymakers and contributing to more informed economic decision-making.
Co-Authors Agung Prabowo Akbar Taufik Amrullah Aprilianti, Dwi Savira Aulia Putri Salsabila Aulia, Aleyda Kania Farra Azka, Muhammad Christianto Credidi Khala Darwis, M. Daffa Rivaldy Diana Nurlaily Diana Nurlaily Dyah Wahyu Apriani Farida Nur Hayati Farida Nur Hayati Ferdy Novri Firdaus, Andi Adam Firman, Fahmi Fauzan Fitria, Irma Fitria, Irma Fitriani, Yustina Hanifatuzzuhro, Retno Lelly Winda Hariyadi, Fahri Dwi Hayati, Farida Nur Hermayanti, Naura Attya Hernanda, Yunissa Irawan, Hairul Irma Fitria Khoiriyah, Nurhastivania Sohifatul Lastiur, Sunrie Kristella Lembang, Gebryani Rante Lumintang, Indah Ayu Magh Heryan Tudaan Muhammad Iqbal Novelinda, Resti Nur Annisa Nurlaily, Diana Padli, Rianto Patricia, Michell Pratomo, Achmad Haryo Raaph, Nadya Alivia Rabbani, Muhammad Abidzaar Rifqi Rama, Luthfy Ahmad Rezki, Surya Muhammad S, Hadiyyan Falakha Salfina Salfina, Salfina Sari, Dewi Leonita Sembiring, Brema Septiandra, Muhammad Rafly Suhartono Suhartono Surya Puspita Sari, Surya Puspita Wijayanti, Anis Fadillah Winda, Retno Lelly Zahra, Kayla Salbina