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All Journal EKSAKTA: Journal of Sciences and Data Analysis Journal of Natural Sciences and Mathematics Research Sistemasi: Jurnal Sistem Informasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jambura Journal of Mathematics Jurnal Varian Jurnal Teknik Informatika (JUTIF) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Enthusiastic : International Journal of Applied Statistics and Data Science Journal of Mathematics, Computation and Statistics (JMATHCOS) Emerging Statistics and Data Science Journal
Kartikasari, Mujiati Dwi
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Enthusiastic : International Journal of Applied Statistics and Data Science

 1 
Forecasting COVID-19 Cases in Indonesia Using Hybrid Double Exponential Smoothing Kartikasari, Mujiati Dwi
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 1 Issue 2, October 2021
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (291.859 KB) | DOI: 10.20885/enthusiastic.vol1.iss2.art1

Abstract

The COVID-19 epidemic has spread throughout countries around the world. In Indonesia, this case was detected in early March 2020, and until now, there is still an increase in positive cases of COVID-19. The purpose of this paper is to predict COVID-19 cases in Indonesia using a time series approach. The method used is H-WEMA method because this method can capture trend data patterns following the conditions of COVID-19 cases in Indonesia. Based on the analysis results, H-WEMA can predict COVID-19 cases very well. The forecasted results of the COVID-19 cases in Indonesia still have an upward trend, so it needs the cooperation of all elements of community to reduce the spread of COVID-19.
Forecasting International Tourist Arrivals in Indonesia Using SARIMA Model Nurhasanah , Deden; Salsabila , Aurielle Maulidya; Kartikasari, Mujiati Dwi
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 1, April 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss1.art3

Abstract

Tourism is an important sector that significantly contributes to the economy, so the tourism sector is a priority development program. International tourist arrivals indirectly contribute to the country's economic growth. The government has an important task to increase the number of foreign tourist visits. One way to encourage an increase in foreign tourist arrivals is by forecasting. In general, the time series data for the arrival of foreign tourists has a seasonal pattern. The forecasting method that can model seasonal data is SARIMA. This study aims to predict the arrival of foreign tourists in Indonesia using the SARIMA model. Forecasting results show that the appearance of foreign tourists to Indonesia has increased every period.
Co-Authors Cahyani, Amalia Rizqi Chaerunnisa, Azzahra Fajriani Destia, Bella Febriani, Atika Dwi Fitriyah, Zakiyatul Herdiantini , Rizka Fitria Inas Rafidah Junita, Tarisya Permata Mulyawati, Saffanah Nur Elvina Mutalip, Nurqalbu Abd. Nurhasanah , Deden PRASMONO, AMIMAH SHABRINA PUTRI Putri, Farah Anindia Qonita, Rosyada Laili Salsabila , Aurielle Maulidya Sulistyawati, Yuni Vatin, Kayyis Wijayanti, Latifah Nur